{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 一、找到持仓增多的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "开始连接数据库...\n",
      "开始查找上次数据...\n",
      "开始导出数据...\n",
      "导出数据到【csv/持有基金个数增多的股票2023-09-20.csv】成功，谢谢使用。\n",
      "导出数据到【csv/基金持有市值增多的股票2023-09-20.csv】成功，谢谢使用。\n",
      "                                            持有基金个数增多的股票                                             \n"
     ]
    },
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>股票名称</th>\n",
       "      <th>【2023-05-29】持有基金个数</th>\n",
       "      <th>【2023-09-20】持有基金个数</th>\n",
       "      <th>【2023-05-29】基金持有市值</th>\n",
       "      <th>【2023-09-20】基金持有市值</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>中际旭创</td>\n",
       "      <td>54</td>\n",
       "      <td>187</td>\n",
       "      <td>10.033896</td>\n",
       "      <td>32.436245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>恒瑞医药</td>\n",
       "      <td>131</td>\n",
       "      <td>238</td>\n",
       "      <td>43.140560</td>\n",
       "      <td>79.743210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>中兴通讯</td>\n",
       "      <td>72</td>\n",
       "      <td>161</td>\n",
       "      <td>15.078356</td>\n",
       "      <td>41.217616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>美的集团</td>\n",
       "      <td>163</td>\n",
       "      <td>223</td>\n",
       "      <td>10.108763</td>\n",
       "      <td>33.667683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>中国平安</td>\n",
       "      <td>224</td>\n",
       "      <td>282</td>\n",
       "      <td>49.470989</td>\n",
       "      <td>51.369882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>新易盛</td>\n",
       "      <td>15</td>\n",
       "      <td>63</td>\n",
       "      <td>0.515779</td>\n",
       "      <td>9.319172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>传音控股</td>\n",
       "      <td>25</td>\n",
       "      <td>70</td>\n",
       "      <td>9.628387</td>\n",
       "      <td>6.781452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>科伦药业</td>\n",
       "      <td>56</td>\n",
       "      <td>97</td>\n",
       "      <td>3.989480</td>\n",
       "      <td>6.958025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>北方华创</td>\n",
       "      <td>55</td>\n",
       "      <td>91</td>\n",
       "      <td>7.129980</td>\n",
       "      <td>17.685491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>长江电力</td>\n",
       "      <td>127</td>\n",
       "      <td>163</td>\n",
       "      <td>7.349044</td>\n",
       "      <td>13.179169</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   股票名称  【2023-05-29】持有基金个数  【2023-09-20】持有基金个数  【2023-05-29】基金持有市值  \\\n",
       "0  中际旭创                  54                 187           10.033896   \n",
       "1  恒瑞医药                 131                 238           43.140560   \n",
       "2  中兴通讯                  72                 161           15.078356   \n",
       "3  美的集团                 163                 223           10.108763   \n",
       "4  中国平安                 224                 282           49.470989   \n",
       "5   新易盛                  15                  63            0.515779   \n",
       "6  传音控股                  25                  70            9.628387   \n",
       "7  科伦药业                  56                  97            3.989480   \n",
       "8  北方华创                  55                  91            7.129980   \n",
       "9  长江电力                 127                 163            7.349044   \n",
       "\n",
       "   【2023-09-20】基金持有市值  \n",
       "0           32.436245  \n",
       "1           79.743210  \n",
       "2           41.217616  \n",
       "3           33.667683  \n",
       "4           51.369882  \n",
       "5            9.319172  \n",
       "6            6.781452  \n",
       "7            6.958025  \n",
       "8           17.685491  \n",
       "9           13.179169  "
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     "output_type": "stream",
     "text": [
      "                                            基金持有市值增多的股票                                             \n"
     ]
    },
    {
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       "      <th></th>\n",
       "      <th>股票名称</th>\n",
       "      <th>【2023-05-29】持有基金个数</th>\n",
       "      <th>【2023-09-20】持有基金个数</th>\n",
       "      <th>【2023-05-29】基金持有市值</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>药明生物</td>\n",
       "      <td>33</td>\n",
       "      <td>27</td>\n",
       "      <td>9.307683</td>\n",
       "      <td>12.909941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>三七互娱</td>\n",
       "      <td>44</td>\n",
       "      <td>44</td>\n",
       "      <td>5.720974</td>\n",
       "      <td>8.498209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>乐普医疗</td>\n",
       "      <td>33</td>\n",
       "      <td>30</td>\n",
       "      <td>1.507028</td>\n",
       "      <td>3.686865</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>法拉电子</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>8.175460</td>\n",
       "      <td>10.028806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>长川科技</td>\n",
       "      <td>23</td>\n",
       "      <td>14</td>\n",
       "      <td>1.966584</td>\n",
       "      <td>3.654628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>中国核电</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>1.087681</td>\n",
       "      <td>2.765879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>康方生物</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>0.921930</td>\n",
       "      <td>2.355526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>华润三九</td>\n",
       "      <td>37</td>\n",
       "      <td>31</td>\n",
       "      <td>20.240894</td>\n",
       "      <td>21.514271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>新泉股份</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>10.897496</td>\n",
       "      <td>12.034464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>万华化学</td>\n",
       "      <td>81</td>\n",
       "      <td>76</td>\n",
       "      <td>15.104807</td>\n",
       "      <td>16.217498</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "   股票名称  【2023-05-29】持有基金个数  【2023-09-20】持有基金个数  【2023-05-29】基金持有市值  \\\n",
       "0  药明生物                  33                  27            9.307683   \n",
       "1  三七互娱                  44                  44            5.720974   \n",
       "2  乐普医疗                  33                  30            1.507028   \n",
       "3  法拉电子                  14                  14            8.175460   \n",
       "4  长川科技                  23                  14            1.966584   \n",
       "5  中国核电                  18                  17            1.087681   \n",
       "6  康方生物                  11                  10            0.921930   \n",
       "7  华润三九                  37                  31           20.240894   \n",
       "8  新泉股份                  20                  20           10.897496   \n",
       "9  万华化学                  81                  76           15.104807   \n",
       "\n",
       "   【2023-09-20】基金持有市值  \n",
       "0           12.909941  \n",
       "1            8.498209  \n",
       "2            3.686865  \n",
       "3           10.028806  \n",
       "4            3.654628  \n",
       "5            2.765879  \n",
       "6            2.355526  \n",
       "7           21.514271  \n",
       "8           12.034464  \n",
       "9           16.217498  "
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     "text": [
      "                                           持有基金个数减少最多的股票                                            \n"
     ]
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       "      <th>股票名称</th>\n",
       "      <th>【2023-05-29】持有基金个数</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>隆基绿能</td>\n",
       "      <td>233</td>\n",
       "      <td>115</td>\n",
       "      <td>50.142500</td>\n",
       "      <td>25.171385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>海康威视</td>\n",
       "      <td>179</td>\n",
       "      <td>94</td>\n",
       "      <td>28.660663</td>\n",
       "      <td>12.511973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>药明康德</td>\n",
       "      <td>157</td>\n",
       "      <td>98</td>\n",
       "      <td>91.996788</td>\n",
       "      <td>61.361496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>山西汾酒</td>\n",
       "      <td>118</td>\n",
       "      <td>62</td>\n",
       "      <td>131.294155</td>\n",
       "      <td>90.643377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>中国中免</td>\n",
       "      <td>85</td>\n",
       "      <td>29</td>\n",
       "      <td>11.916375</td>\n",
       "      <td>3.797653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>泸州老窖</td>\n",
       "      <td>229</td>\n",
       "      <td>185</td>\n",
       "      <td>181.712074</td>\n",
       "      <td>146.026241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>广联达</td>\n",
       "      <td>54</td>\n",
       "      <td>18</td>\n",
       "      <td>18.719044</td>\n",
       "      <td>7.476291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>东方财富</td>\n",
       "      <td>187</td>\n",
       "      <td>152</td>\n",
       "      <td>41.233051</td>\n",
       "      <td>27.931376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>中控技术</td>\n",
       "      <td>82</td>\n",
       "      <td>47</td>\n",
       "      <td>4.929328</td>\n",
       "      <td>2.659053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>昆仑万维</td>\n",
       "      <td>54</td>\n",
       "      <td>20</td>\n",
       "      <td>3.986916</td>\n",
       "      <td>0.509732</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "   股票名称  【2023-05-29】持有基金个数  【2023-09-20】持有基金个数  【2023-05-29】基金持有市值  \\\n",
       "0  隆基绿能                 233                 115           50.142500   \n",
       "1  海康威视                 179                  94           28.660663   \n",
       "2  药明康德                 157                  98           91.996788   \n",
       "3  山西汾酒                 118                  62          131.294155   \n",
       "4  中国中免                  85                  29           11.916375   \n",
       "5  泸州老窖                 229                 185          181.712074   \n",
       "6   广联达                  54                  18           18.719044   \n",
       "7  东方财富                 187                 152           41.233051   \n",
       "8  中控技术                  82                  47            4.929328   \n",
       "9  昆仑万维                  54                  20            3.986916   \n",
       "\n",
       "   【2023-09-20】基金持有市值  \n",
       "0           25.171385  \n",
       "1           12.511973  \n",
       "2           61.361496  \n",
       "3           90.643377  \n",
       "4            3.797653  \n",
       "5          146.026241  \n",
       "6            7.476291  \n",
       "7           27.931376  \n",
       "8            2.659053  \n",
       "9            0.509732  "
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     "text": [
      "                                           持有基金市值减少最多的股票                                            \n"
     ]
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       "      <th>股票名称</th>\n",
       "      <th>【2023-05-29】持有基金个数</th>\n",
       "      <th>【2023-09-20】持有基金个数</th>\n",
       "      <th>【2023-05-29】基金持有市值</th>\n",
       "      <th>【2023-09-20】基金持有市值</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>山西汾酒</td>\n",
       "      <td>118</td>\n",
       "      <td>62</td>\n",
       "      <td>131.294155</td>\n",
       "      <td>90.643377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>泸州老窖</td>\n",
       "      <td>229</td>\n",
       "      <td>185</td>\n",
       "      <td>181.712074</td>\n",
       "      <td>146.026241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>五粮液</td>\n",
       "      <td>297</td>\n",
       "      <td>292</td>\n",
       "      <td>201.926435</td>\n",
       "      <td>166.390467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>贵州茅台</td>\n",
       "      <td>450</td>\n",
       "      <td>445</td>\n",
       "      <td>297.337083</td>\n",
       "      <td>265.824452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>药明康德</td>\n",
       "      <td>157</td>\n",
       "      <td>98</td>\n",
       "      <td>91.996788</td>\n",
       "      <td>61.361496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>隆基绿能</td>\n",
       "      <td>233</td>\n",
       "      <td>115</td>\n",
       "      <td>50.142500</td>\n",
       "      <td>25.171385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>爱尔眼科</td>\n",
       "      <td>115</td>\n",
       "      <td>99</td>\n",
       "      <td>62.114565</td>\n",
       "      <td>37.245115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>九洲药业</td>\n",
       "      <td>18</td>\n",
       "      <td>11</td>\n",
       "      <td>21.981511</td>\n",
       "      <td>4.883939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>海康威视</td>\n",
       "      <td>179</td>\n",
       "      <td>94</td>\n",
       "      <td>28.660663</td>\n",
       "      <td>12.511973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>泰格医药</td>\n",
       "      <td>54</td>\n",
       "      <td>21</td>\n",
       "      <td>23.837707</td>\n",
       "      <td>9.450237</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   股票名称  【2023-05-29】持有基金个数  【2023-09-20】持有基金个数  【2023-05-29】基金持有市值  \\\n",
       "0  山西汾酒                 118                  62          131.294155   \n",
       "1  泸州老窖                 229                 185          181.712074   \n",
       "2   五粮液                 297                 292          201.926435   \n",
       "3  贵州茅台                 450                 445          297.337083   \n",
       "4  药明康德                 157                  98           91.996788   \n",
       "5  隆基绿能                 233                 115           50.142500   \n",
       "6  爱尔眼科                 115                  99           62.114565   \n",
       "7  九洲药业                  18                  11           21.981511   \n",
       "8  海康威视                 179                  94           28.660663   \n",
       "9  泰格医药                  54                  21           23.837707   \n",
       "\n",
       "   【2023-09-20】基金持有市值  \n",
       "0           90.643377  \n",
       "1          146.026241  \n",
       "2          166.390467  \n",
       "3          265.824452  \n",
       "4           61.361496  \n",
       "5           25.171385  \n",
       "6           37.245115  \n",
       "7            4.883939  \n",
       "8           12.511973  \n",
       "9            9.450237  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import display\n",
    "from dataModel import JJs, Stocks, db\n",
    "from colorama import Fore as fore\n",
    "\n",
    "old_date = \"2023-05-29\"\n",
    "new_date = \"2023-09-20\"\n",
    "\n",
    "db.close()\n",
    "print(\"开始连接数据库...\")\n",
    "db.connect()\n",
    "sSelect = Stocks.select()\n",
    "print(\"开始查找上次数据...\")\n",
    "olds = sSelect.where((Stocks.date == old_date))\n",
    "aups = []\n",
    "bups = []\n",
    "adowns = []\n",
    "yesterday = int(new_date.split(\"-\")[-1]) - 1\n",
    "yesterday = \"-\".join(new_date.split(\"-\")[:-1]) + f\"-{yesterday}\"\n",
    "for old in olds:\n",
    "    name = old.name\n",
    "    new = sSelect.where(\n",
    "        (Stocks.date == new_date or Stocks.date == yesterday),\n",
    "        (Stocks.name == name),\n",
    "        (Stocks.n >= 10),\n",
    "    )\n",
    "    if new:\n",
    "        new = new[0]\n",
    "        data = {\n",
    "            \"股票名称\": new.name,\n",
    "            f\"【{old_date}】持有基金个数\": old.n,\n",
    "            f\"【{new_date}】持有基金个数\": new.n,\n",
    "            f\"【{old_date}】基金持有市值\": old.money,\n",
    "            f\"【{new_date}】基金持有市值\": new.money,\n",
    "        }\n",
    "        if new.n > old.n:\n",
    "            aups.append(data)\n",
    "        elif round(new.money, 3) > round(old.money, 3):\n",
    "            bups.append(data)\n",
    "        else:\n",
    "            adowns.append(data)\n",
    "\n",
    "\n",
    "def asort(stock):\n",
    "    \"\"\"获取排序的key，持有基金个数按数量绝对值差排序\"\"\"\n",
    "    return stock[f\"【{new_date}】持有基金个数\"] - stock[f\"【{old_date}】持有基金个数\"]\n",
    "\n",
    "\n",
    "def bsort(stock):\n",
    "    \"\"\"获取排序的key，基金持仓市值按比例排序\"\"\"\n",
    "    return stock[f\"【{new_date}】基金持有市值\"] - stock[f\"【{old_date}】基金持有市值\"]\n",
    "\n",
    "\n",
    "aups = sorted(aups, key=asort, reverse=True)\n",
    "bups = sorted(bups, key=bsort, reverse=True)\n",
    "adowns = sorted(adowns, key=asort)\n",
    "bdowns = sorted(adowns, key=bsort)\n",
    "\n",
    "dfa = pd.DataFrame(aups)\n",
    "dfb = pd.DataFrame(bups)\n",
    "dfc = pd.DataFrame(adowns)\n",
    "dfd = pd.DataFrame(bdowns)\n",
    "\n",
    "print(\"开始导出数据...\")\n",
    "patha = f\"csv/持有基金个数增多的股票{new_date}.csv\"\n",
    "dfa.to_csv(patha, encoding=\"utf-8\")\n",
    "print(f\"导出数据到【{patha}】成功，谢谢使用。\")\n",
    "pathb = f\"csv/基金持有市值增多的股票{new_date}.csv\"\n",
    "dfb.to_csv(pathb, encoding=\"utf-8\")\n",
    "print(f\"导出数据到【{pathb}】成功，谢谢使用。\")\n",
    "db.close()\n",
    "if len(dfa):\n",
    "    print(f\"{'持有基金个数增多的股票':^100}\")\n",
    "    display(dfa[:10])\n",
    "else:\n",
    "    print(f\"{'好惨，没有基金持有个数增多的股票':^100}\")\n",
    "if len(dfb):\n",
    "    print(f\"{'基金持有市值增多的股票':^100}\")\n",
    "    display(dfb[:10])\n",
    "else:\n",
    "    print(f\"{'好惨，没有基金持有市值增多的股票':^100}\")\n",
    "print(f\"{'持有基金个数减少最多的股票':^100}\")\n",
    "display(dfc[:10])\n",
    "print(f\"{'持有基金市值减少最多的股票':^100}\")\n",
    "display(dfd[:10])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 二、绘制股票的曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "开始查找股票数据...\n",
      "数据查找完毕，开始绘图...\n"
     ]
    },
    {
     "data": {
      "image/png": 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tmN5++231799fKSkpSklJUdeuXTVw4EClpKRo0KBB1RqBbdy4UbfddpsGDhyoU045Rf/4xz8kSZs2bVJRUZFCQ0P1n//8R263W8cdd5xuueUW/fDDD/4trnymT5+uLVu2aO3atcrPz9cbb7yhxMRE5efnKz8/X++99562b9+uO+64o8p1p5xyil5++WVt3rxZkZGR/tD7/PPPa8uWLdq0aZN27typnTt36ueff5YkrVu3Ths2bKj1hxNPP/20P1x36NChxvNsNptOO+00/88yNDRU48eP9798U6qnTZtWbc/lQ/nHP/6h4cOHa/DgwbrwwguPuPc3AAB/xEgzAMBUl19+uX869uGEhYXpyy+/1ODBg2s8Jy8vT5dccokuuOAC/2hlSEiIduzYoXXr1mnmzJlasmSJf5RUqhwtPnj7o127dvnXCt92223+qcbZ2dlq27atXC6XbDabrFar2rdvr1dffVW//PJLlTruuecefyOv8vJyhYWFaeXKlYfcHulf//qX7rjjDh1//PH69ttvdc0111SZ9nzllVfqyiuvlCTNnTtXkyZN0iOPPKL58+fr119/rbJHcXx8vMaPH69u3brpww8/VHh4uKxWq2JjY5WXl6cpU6bozjvv1LRp06rU0LVrV1133XXVauvcubP+8pe/aN++ffr3v/9d5b0uXbrUat24T1BQkAoLC/XKK68c9p9hWFiYvvvuO0mVDc7mzp2r9957T9HR0ZIqR+bPO+88TZgwoVbPveyyy9S7d2+NGzdO1157bZWO7JL8U9UBAKgJI80AAFOddNJJOuOMM454ns1m07hx46p0qJZ+X+NcWFio999/X06nU9OnT/e/f8EFF6i4uFgDBgzQiy++qJdfftm/Rjc7O1v/+9///Ps+FxYWKj8/X6eddpqioqKUnJysyy67THa7XTfddJPWrl2r4OBgrVy58rC1HmpNcU1uvPFG/fzzz1q6dKnGjBmj1atXy+12yzAMdenSRe+//768Xq+Ki4t16qmn6vLLL9e2bdu0ePHiKoHZ57bbbtOsWbO0d+/eKse/+uorhYWF6b777qt1bZI0cOBAzZkzR2VlZXW67o/+8pe/aOHChbr55pslVXYI/2Nn7j96+umnZbfbdc455ygnJ0c333yzfvzxR7311lu1eqZhGOrQoYN/n+xDeeedd3T66acrLy+v9t8MAKBFYaQZABBwnE6nPB7PYc/Jy8vT9OnT9fnnn+vhhx/WSy+9pNatW+u6667T0qVLFR0dreDgYHm9Xs2aNUtOp9PfPGvnzp3q2rWrnn/+eUVGRurEE0+UVDkVeN26dQoJCVFoaKiCgoJktVpltVp1+eWXq0OHDvq///s/tWnTpkotB9daUlKi/fv3KyIiQlar1d/tuaioSA6HQ16v1z/VvEuXLv4105mZmQoNDZXVavVPu/Z6vSotLVVBQYH/5+J774+BecOGDZIq945+++23VVJSouzsbLndbm3btk0ff/yxzj//fO3bt0979+5VdHR0le2zpMqQ6XQ6q6w5PvPMMzVt2jT/BwG+6fGH63ru66g9c+ZMXXjhhdXez83N1bvvvquioiKdeuqpNd4nMjJSX3zxhUaMGKHExETZbDYtWrRIrVu3rvEaH5fLVa1Gi8WiFStWaMOGDQoPD5dhGPr222+1atUqxcbGHvGeAICWyWLUtN8EAAAmmT59um644QaVlJQoPDz8kOfMnz9f1113nb7//nt/A6qFCxfqs88+06pVq5SWlqaCggKVlZXJ4/H49/i1WCzas2ePOnTooDfffFNr1qzRSy+9VGMtGzZs0NChQ+XxePTVV19V2Rtakp588km9/vrrkqS0tDQtWLCgShfumhzcgXvFihU68cQTFRwc7A+ch+LrND527Fh9/fXXVd7r1auXMjIyFBoaethA6wvGZ511VpUO4X/961/1wQcfKDc3V9u3b1fHjh2rXTt16lTNnDlT+/fvr9LZ/I/cbrfOPPNMLViw4JAfflgsFnXt2lXffPNNlT2lV65cqQ0bNig/P1/p6elas2aNFi9erLCwMJ1++un66aeflJmZqeTkZA0cOFDt2rVTUFCQbrnlFv82YT7jxo1TVFSUPv74Y/+x9957T9dee22VteDBwcF67rnndPvtt9f4/QAAWjZCMwCgySosLPSvdW1IX375pUaMGFFthFmqDOpz5szRZZdd5g/XbrfbP0p9KBUVFfJ6vbVqZNVYFi9erIULF+qCCy7wfwjxR59//rkWLFigSy+9VMOHD6/3GhYsWKDTTjtNXbp0Ub9+/TRkyBCdcsopGjFihL8x3KpVq/TDDz9o6dKlWr9+vaKjo7V48eJaP8Pj8VQLzYfr5g0AAKEZAAAEDJfLddjRdgAAGhuhGQAAAACAGjAfCQAAAACAGhCaAQAAAACoQUBsOeX1epWZmamoqKjDdvwEAAAAAKA+GIahoqIidezY8bBNIQMiNGdmZioxMdHsMgAAAAAALUx6eroSEhJqfD8gQnNUVJSkymIbY+sQAAAAAEDLVlhYqMTERH8erUlAhGbflOzo6GhCMwAAAACg0RxpiTCNwAAAAAAAqAGhGQAAAACAGhCaAQAAAACoQUCsaQYAAACA+uLxeORyucwuAyYLCgqSzWY75vsQmgEAAAA0C4ZhKCsrSw6Hw+xSECBiY2PVvn37Izb7OhxCMwAAAIBmwReY4+PjFR4efkxBCU2bYRgqLS1VTk6OJKlDhw5HfS9CMwAAAIAmz+Px+ANzmzZtzC4HASAsLEySlJOTo/j4+KOeqk0jMAAAAABNnm8Nc3h4uMmVIJD4fh+OZY07oRkAAABAs8GUbBysPn4fCM0AAAAAANSA0AwAAAAAqJM5c+Zozpw5db5u/vz5uvXWW5Wbm3vUzzYM46ivPRqEZgAAAAAw2ffff6/BgwdXOz5lyhS9+OKLR7x+2rRpuv/++494ntvtltvt1vTp03XBBRdUee9f//qXJk2aJElyOp013iMrK0vXXnutbrrpJq1Zs+aIz/Txer165JFH9Nprr2nv3r2HPe/WW2/V/v37NWbMGM2dO1ePP/64Zs+eLUkaMmSIvvnmm1o/91jRPRsAAAAATBYeHq6oqChJlSOpTqdTwcHBCg4O9h93Op2y2+2yWq1yu92yWCz+jtDff/+9xo4dW+2+B18jSe+8845mzJih/fv3y+FwaOTIkf5zs7KyVFRUpJNOOklWq1U///xztfu53W5NnjxZI0aM0AMPPKCzzz5bX375pVJSUo74PT7zzDNKT0/X448/rokTJ2rx4sWKjY2tdp7VatXo0aO1bds2hYSEyGq1au/evbrzzjtVUFCgbdu2qUuXLtq2bZsMw1B0dLTatWt3xOcfLYvR2GPbh1BYWKiYmBgVFBQoOjra7HIAAAAANDHl5eXauXOnunbtqtDQULPLqTWv1ytJWrp0qR544AH9+OOP2rZtmwYMGKCQkBCVl5fLZrMpKChIJSUlWr58uVJSUvT444/r2Weflc1mk9frVVFRkWJiYqrd3+Vy6bvvvtOIESOqHH/33Xc1b948ffLJJ/5jr7/+upYsWaJ33333kLWWl5fr0ksv1a5du7RgwQJFR0drzpw5uvrqq3Xffffpzjvv9G/z9EdffvmlJkyYoDlz5ujPf/6zpkyZohUrVmju3LlKSEiocu4zzzyj5557Tna7XXl5eWrdurXsdrvi4uL04IMP6m9/+5sGDhyo7du3q7i4WA8++KCmTJlSY801/V7UNocyPRsAAABAs2QYhkqdblNetR2b3LJliyZPnqwnn3xSW7Zs0VVXXSWn06ny8nIVFBToqquu0quvvqqCggK53W7/iO5DDz2koqIiORwO3XzzzbrwwgvlcDiqvUpKSqoFZp958+apf//+/tfjjz9eY52bN2/WSSedpH379umHH37wh8zzzz9f8+fP17vvvqsuXbrovvvu04oVK6r8M3jppZd00UUX6YUXXtDgwYP18ssv6/XXX9egQYPUv39//fOf/1R5ebn/mvvvv1/btm1Tp06d1LZtW/3zn//UxIkTtXr1ar333nt69NFH9dlnn2ny5Mm69NJLawzM9YXp2QAAAACapTKXR30fnm/Kszc89ieFBx85bvXu3VsfffSRlixZogceeEDvvvuu7r33Xr399tuyWCwqKSnRhx9+qHvuuUdS5cj0Tz/9pAEDBkiS5s6dqxdffFHt2rVTUlJSlXvv3r1bO3furHbcp0uXLrrkkkv8X//222+HPG/evHk6//zzde211+r7779XcnJyla2cPB6PIiMj9cwzz+jVV19VUlKShgwZosWLF+u+++7TsmXL9Pbbb+uyyy7T+vXrdeedd+rWW2/Vv//9b7344ot64IEH9PDDD2vatGm67rrr9PPPP+vqq6/WpZdeqh9//FFRUVH6/vvv9eSTT2revHm69NJLJUkOh6NBp2X7EJoBAAAAIADk5+dr8uTJevTRR/XMM8/41yFLleF67ty5ateunX+a8aJFi3TxxRerV69eSk1NrXY/u92ukJAQ/9cul0sej8d/rH379jrttNP87xcWFiozM9N/rtvtVlhYmE4//XTNmzdPY8aM0b59+xQZGanMzEyNGDFCWVlZ8ng8cjgcatOmja666ir/KHtISIhsNpuWL1+u/v37S6pcu+17vsVi0Z133qnx48fr6aef1vnnny9JioyM1K233qrx48frxBNP1NixY9WhQwctW7ZMo0eP1sKFC3XppZcqMzNTycnJ9fXjrxGhGQAAAECzFBZk04bH/mTas2srMzNT77zzjtasWaNevXopNjZWXq+3SmiW5G/8ZbVa9f777+v222/X5MmT9f7771dp6OXj8XiqjAh//fXXuv/++xUaGiqv16t169YpPT1dwcHBkqT09HTZbDalpKTI6XRqwIABmjlzpmw2m8aMGaPy8nK1bt1aVqu1Sm02m01RUVEqKytTWFiY/5mDBw/WggULqn0PB9ckSV27dtUbb7zh/7pXr15KTk7WU089pfXr1+vPf/6zhgwZoiFDhujqq6/WwIEDZRiGNmzYoNtvv73WP+ejRWgGAAAA0CxZLJZaTZE207x583TeeefpxBNP1KhRozRr1iz/VOWgoCD/eUVFRRowYIDKy8u1Z88evfTSS/r888/ldDq1ePFi/fLLL9XubbdX/d7PO+88nXfeeXK73brpppvUtWtXffHFF3rxxRd1ySWXKDMzU+PGjdNrr72m4cOHV7vfpZdequXLl/u7d+fm5vqnfrtcLp1wwglHtXfzH/Xp00eGYSgjI0MJCQnq3LmzcnJytH//foWHh6tnz5769ttvtWnTJvXt2/eYn3ckNAIDAAAAAJOMHj1aq1at0tNPP+0fvX3ssce0bNkyrVmzxt/Qq0ePHlq7dq1cLpfi4+P122+/6ZRTTpEkbdiwQUlJSdVeHo+n2vN++OEHjRgxQtnZ2frggw8kSc8++6zy8vI0cOBAvfPOOxo/fryuvfZaLVu2rMq1n3zyiW655RZt3LhRv/zyi9q2batdu3Zp9uzZuuGGGzRz5sx6+Zns3r1bH330kYYPH660tDRNnz5dp59+usLDwyVJF110ka6//nqNGTOmygcLDYXQDAAAAAAmCQ8PV58+faodf+ONN/Svf/2rxusOnuLct29f7dq1q9rLt4ezz5w5c3TDDTforrvu0pVXXqmhQ4eqf//+ys3N1fjx49WvXz999913WrlypZxOp6ZPn16lC3hQUJA+/vhjvf3221Xu+9lnn2nBggX+ad6HYxhGrTqLb9u2TR6PRyNGjNBtt92mYcOG+T8EGDt2rNLS0nTuuece8T71IbDnKgAAAABAC+D1eqsE4QkTJlTpZu3bz/lQ1/1RVlaWUlNT5fF4qozEnn/++Ro3bpwsFovsdrsuvPBCSVJSUpK++OIL9e7d23/PGTNmVAnBTqdTVqtV06ZNq7bf8eeff663337bv23U4fbJLi0trbK9VE2mTJmi4cOH68orr9SAAQM0ffp0RUVF6bTTTtNFF12kc845R4888oiGDRumfv36HfF+x4LQDAAAAAAmeuSRR/Txxx9r7Nix/mMjR47UyJEjtWPHDt1+++1KS0tTmzZtql3rdDqrHSsuLtZ5552nyZMnV7vmu+++06233qrQ0FD/dPDIyEhddNFF/nPcbrdGjx6t6dOn+49NmjRJixYtqhLC7Xa7EhISJEkTJ06Uy+XSSSedpNmzZ9f4vZaUlMjr9aq0tNQ/3fqPPv/8c3300UdatWqVnnjiCV1yySXKysrSfffdp7/97W967rnndOONN+qhhx7S0KFD9e9//1sXX3xxjc88VhajtrtuN6DCwkLFxMSooKDAv0k2AAAAANRWeXm5du7cqa5dux52pDMQrVixQjk5OTrttNOqrdH1er2aNm2aTj75ZA0dOrTW9/R4PNWmZzcV77zzjqxWqyZNmuTfnsowDL3wwgs655xz1KNHD/+5c+bM0dlnn13j1PDD/V7UNocSmmspLa9Ud89KbbD7hwXbdNPY4zTiuLgGewYAAADQXDXl0IyGUx+hmenZtVTm8mj57vwGfcbyXfn66LphGtS5VYM+BwAAAABQO4TmWuoQG6rXJw9usPt/tDRdC7fk6up3l+nzm0aoW9vIBnsWAAAAAKB2CM21FB0apDP7d2iw+4/q0VaXvLlEazIKdMXbSzX7phGKj2ZaCQAAAACYiX2aA0REiF1vTzleSW3ClZFfpinvLFNRucvssgAAAACgRSM0B5C4yBC9d/UwxUUGa8PeQt34wQo53Yfejw0AAAAA0PAIzQGmc5twvTPlBEUE27RoW57u+XS1vF7TG5wDAAAAgN+cOXM0Z86co7rW4XDU6ryCggJt2LChyrH169dr48aNR/Xco0VoDkADEmL0+uVDZLda9MXqTD35TeP+UgAAAABoXN9//70GD67eeHjKlCl68cUXj3j9tGnTdP/99x/xPLfbLbfbrenTp+uCCy6o8t6//vUvTZo0SZLkdDprvEdWVpauvfZa3XTTTVqzZs0Rn3mwGTNm6Oyzz67VuZ9++qnGjh2r4uJi/7HnnntOb775Zp2eeazq3AgsKSlJu3fvrnLMMAytXLlSV199tTZv3qxRo0bpgw8+UHx8fL0V2tKM6tFWz00YqLtmrtaMX3aqXXSorhvdzeyyAAAAADSA8PBwRUVFSarMV06nU8HBwQoODvYfdzqdstvtslqtcrvdslgsstlskipD99ixY6vd9+BrJOmdd97RjBkztH//fjkcDo0cOdJ/blZWloqKinTSSSfJarXq559/rnY/t9utyZMna8SIEXrggQd09tln68svv1RKSkq1c4uKiuRyuao8f9y4cVqwYIFyc3MVFhYmSfJ6vXK5XAoLC1N4eLj/+vfee0/33HOPLrvsMqWmpspisWjfvn0KDg7W7NmzJUkul0sbN2487D7Lx8yooy5duhjz58838vPz/S+Px2MkJSUZDz74oJGenm6ce+65xqWXXlrrexYUFBiSjIKCgrqW0+y9vmCb0eX+r4wu939l/GdVhtnlAAAAAAGprKzM2LBhg1FWVmZ2KXXi8XgMj8djLF682BgzZozh9XqNLVu2GCEhIUZ0dLQRHBxshIWFGdHR0YbNZjNWrVplGIZhPPbYY0ZkZKQRExNjREVFGZKMmJiYaq/w8HBj0aJF1Z77zjvvGBMnTqxy7LXXXjOuvPLKGmstKyszzj//fGPQoEH+7DZ79mwjNjbWePLJJ43S0tIq5994441GUFCQv86aag0PDzfsdrvxj3/8w3/tggULDLvdbjgcDqOiosLweDyGYRjGn/70J+P99983DMMwvF7vEf95H+73orY51GIYRp0WzCYlJem7775Tjx49/Md+/PFHnXfeecrLy5PdbtfKlSs1cuRI5ebmKiIi4oj3LCwsVExMjAoKChr2E4ImyDAMPf7VRr29aKeCbBa9M+UEjewRZ3ZZAAAAQEApLy/Xzp071bVrV4WGNp2tWzdt2qTHHntMxcXFWr58uc444wzde++96tevnyTpxhtv1IknnqgpU6bUeI8HHnhA27Zt02effVbr57777ru68847lZCQ4D+Wn5+v008/Xe+++2618zdv3qxLL71UERER+uKLLxQbG+t/b+nSpbr88suVn5+vKVOmaOLEiRoyZMghn7tt2zb16NFDh4uhXq9XI0aM0Lp161RcXKyioiINHz5ckrRjxw61bdvWP/q+ZMkSRUZG1nivw/1e1DaHHtU+zY8++qjmzJmjnj176sMPP9SiRYt0wgknyG6vvF1KSoo8Ho9WrlypUaNGHc0jcIDFYtHfzu6jnKJyfbVmr254f7lm3jBc/TvFmF0aAAAA0DQ4Sw7/vi1Esh2IRm6n5D3M1q8WqxRUOa1YhiG5SqufE3zkgUOf3r1766OPPtKSJUv0wAMP6N1339W9996rt99+WxaLRSUlJfrwww91zz33SKoMlD/99JMGDBggSZo7d65efPFFtWvXTklJSVXuvXv3bu3cubPacZ8uXbrokksu8X/922+/HfK8efPm6fzzz9e1116r77//XsnJybJYLP73PR6PIiMj9cwzz+jVV19VUlJSjaG5Nv75z39WWRJss9m0fv36akH74OnpDemoQnPXrl21detW3X///br22ms1ZMgQxcX9PvpptVrVqlUrZWdnH/L6iooKVVRU+L8uLCw8mjJaDKvVomkXJyuv2KnFO/I05Z1lmnPzCCW2Dj/yxQAAAEBL92THw78/4V2p3/mVf/7hMenXl2o+t+Mg6foFlX8uzZOeO676OY8WHE2Vys/P1+TJk/Xoo4/qmWee8a8DlirD9dy5c9WuXTv/iOmiRYt08cUXq1evXkpNTa12P7vdrpCQEP/XLpdLHo/Hf6x9+/Y67bTT/O8XFhYqMzPTf67b7VZYWJhOP/10zZs3T2PGjNG+ffsUGRmpzMxMjRgxQllZWfJ4PHI4HGrTpo2uuuqqKuE2MzNTnTp1qhZufQOuktSmTRt/djQMQx9++KFeeukl/+i67+fQvXv3at/jweG9odQ5NC9atEidOnWSJN1+++0aNmyY+vbtWy31G4ZR4zfw1FNP6e9///tRlNtyhdhteuOKIbr49cXalFWkK95eqs9uHK42kSFHvhgAAABAwMrMzNQ777yjNWvWqFevXoqNjZXX660SmqXfR1atVqvef/993X777Zo8ebLef//9Kg29fDweT5VM9vXXX+v+++9XaGiovF6v1q1bp/T0dAUHB0uS0tPTZbPZlJKSIqfTqQEDBmjmzJmy2WwaM2aMysvL1bp1a1mt1iq12Ww2RUVFqaysTGFhYVWe6Qv45eXlstvt/unZbrdbkrR8+XKdf/75Vb7HBQsWVBlk9dm2bVu1n0djqHNo9gVmSf557J07d9bChQv9x32fNLRv3/6Q95g6daruvvtu/9eFhYVKTEysayktTnRokP599Qm64NVftXNfia5+d5k+vv5EhQcf1YQBAAAAoGX4a+bh37cdNBB1ysPS2Kk1n2s5KMiGtznyvY9g3rx5Ou+883TiiSdq1KhRmjVrlh5++GFNmzZNQUFB/vOKioo0YMAAlZeXa8+ePXrppZf0+eefy+l0avHixfrll1+q3fvg0VxJOu+883TeeefJ7XbrpptuUteuXfXFF1/oxRdf1CWXXKLMzEyNGzdOr732mn8N8cEuvfRSLV++3N+9Ozc31z/12+Vy6YQTTqi2d/Mfg/+h/HEUOioq6pChuX///ke8V0Oo0z7NX3/9tXr16uX/Oi0tTeHh4Tr55JO1bNky/6cFq1atkt1u16BBgw55n5CQEEVHR1d5oXbaRYfqvWtOUGx4kFZnFOiWD1fK5fGaXRYAAAAQuIIjDv+yHRQu7cGHP9e3nlmSLJZDn1MHo0eP1qpVq/T000/7A+Zjjz2mZcuWac2aNXI4HHI4HOrRo4fWrl0rl8ul+Ph4/fbbbzrllFMkSRs2bFBSUlK1l8fjqfa8H374QSNGjFB2drY++OADSdKzzz6rvLw8DRw4UO+8847Gjx+va6+9VsuWLaty7SeffKJbbrlFGzdu1C+//KK2bdtq165dmj17tm644QbNnDmzTt97Xa1bt67Kq7HUKTQff/zxyszM1IwZM7Rz50499dRTuvLKKzVy5Ei1bdtWjzzyiDIyMvTYY4/pggsuqLLHFurPcW0j9daVxys0yKofN+dq6uy1h+0+BwAAACAwhYeHq0+fPtWOv/HGG/rXv/5V43UHT03u27evdu3aVe31xxHcOXPm6IYbbtBdd92lK6+8UkOHDlX//v2Vm5ur8ePHq1+/fvruu++0cuVKOZ1OTZ8+vUrOCAoK0scff6y33367yn0/++wzLViwwD/N+2BHyilut7tWo9FS5Ujzwa/GUqd5vfHx8Zo5c6buuusu3XvvvTrnnHP07LPPymq16tNPP9VVV12ladOmafTo0XrrrbcaqmZIGtKllV6+ZLCuf3+5PluRofbRobrnT72OfCEAAACAgOP1eqsE4QkTJlTpZu31Hnp26aGOZ2VlKTU1VR6Pp8oU7/PPP1/jxo2TxWKR3W7XhRdeKKlyW+EvvvhCvXv39t9zxowZVUKw0+mU1WrVtGnTqm3d9Pnnn+vtt99WeXm5JFV53zcb+Y/1Goah2267Tf/5z390/PHHH/L7crvdcrlc/mv+OLpssVjk9XrlcrmqfJ/1rc6LYc866yydddZZ1Y4PHjxYq1evrpeiUDun9W2nJ88foAdmr9XLP25Tu+gQXT48yeyyAAAAANTBI488oo8//lhjx471Hxs5cqRGjhypHTt26Pbbb1daWpratGlT7Vqn01ntWHFxsc477zxNnjy52jXfffedbr31VoWGhvpHeCMjI3XRRRf5z3G73Ro9erSmT5/uPzZp0iQtWrSoSji12+3+fZ4nTpwol8ulk046SbNnz/afExISogcffND/LJercjuv8vJyTZw4USeddJLOPffcat+Db8elF198UdOmTVOnTp2q7CktVfbbOu6443T99dc3aKNpixEA83pru6k0Du1f32/V899tkcUivXbZYJ3Zv4PZJQEAAACNqry8XDt37lTXrl2rjYQGuhUrVignJ0ennXZatRFTr9eradOm6eSTT9bQoUNrfU+Px9MoexgHusP9XtQ2h9J2uRm47ZTuyios10e/pen2T1L1wTUhOqFra7PLAgAAAFALQ4YMqfE9q9Wqe++9t873JDDXnzo1AkNgslgsenx8f53Rt52cbq+u/fcybc4qMrssAAAAAGjyCM3NhM1q0b8uGaShXVqpsNytK99eqkxHmdllAQAAAI0qAFafIoDUx+8DobkZCQ2yacaVQ9U9PlJZheW68u2lcpRWbwwAAAAANDe+tcClpaUmV4JA4vt9OJbu2qxpbmZiw4P176tP0IWv/qqtOcW67r3lev+aYQoNYk0DAAAAmi+bzabY2Fjl5ORIqtz/+OAtnNCyGIah0tJS5eTkKDY29pjWeNM9u5nalFWoCa8vVlG5W2f0bafXJg+Rzcp/NAAAANB8GYahrKwsORwOs0tBgIiNjVX79u0P+QFKbXMoobkZW7IjT1e8tVROj1eXDeus/zuvP5+2AQAAoNnzeDz+/YDRcgUFBR12hJktp6ATu7XRPyel6JaPVurD39LUPjpUt53aw+yyAAAAgAZls9nYcgn1hkZgzdxZAzro0XP6SZKmfbdFs5alm1wRAAAAADQdhOYW4MoRSbp57HGSpKlz1uqHTdkmVwQAAAAATQOhuYW490+9dOHgBHm8hm7+cKVWpeWbXRIAAAAABDxCcwthsVj09IUDNKZnW5W7vLr63WXanltsdlkAAAAAENAIzS1IkM2qVy8brIEJMcovdenKt5cqp7Dc7LIAAAAAIGARmluYiBC73p5yvJLahCsjv0xXvrNMheW04wcAAACAQyE0t0BxkSF67+phiosM1sa9hbrv0zVmlwQAAAAAAYnQ3EJ1bhOuNy4fKkn6flO2yl0ekysCAAAAgMBDaG7BBneOVZuIYLk8hjbsLTS7HAAAAAAIOITmFsxisSg5MVaStDrdYWotAAAAABCICM0tXAqhGQAAAABqRGhu4fwjzRkF5hYCAAAAAAGI0NzCJSfESJJ27iuRo9RpcjUAAAAAEFgIzS1cbHiwktqES2K0GQAAAAD+iNAM1jUDAAAAQA0IzaCDNgAAAADUgNAMf2hOTXfIMAxziwEAAACAAEJohvp2iFaQzaK8Eqcy8svMLgcAAAAAAgahGQoNsqlPh2hJ0uoMh7nFAAAAAEAAITRDkpScECuJdc0AAAAAcDBCMyRVXdcMAAAAAKhEaIYkKSUxRpK0dk+B3B6vydUAAAAAQGAgNEOS1C0uUlEhdpW7vNqSXWx2OQAAAAAQEAjNkCRZrRYNPDDaTDMwAAAAAKhEaIafrxlYaprD1DoAAAAAIFAQmuHnawbGSDMAAAAAVCI0w2/QgdC8JbtIJRVuc4sBAAAAgABAaIZffHSoOsSEymtI6/YUmF0OAAAAAJiO0Iwq/Oua2a8ZAAAAAAjNqIp1zQAAAADwO0IzqkjxheZ0pmcDAAAAAKEZVQxIiJHFIu1xlCmnqNzscgAAAADAVIRmVBEZYleP+EhJjDYDAAAAAKEZ1fw+Rdthah0AAAAAYDZCM6qhGRgAAAAAVCI0oxrftlOr0x3yeg1ziwEAAAAAExGaUU2v9lEKsVtVWO7WzrwSs8sBAAAAANMQmlFNkM2qAZ1iJLGuGQAAAEDLRmjGISXTDAwAAAAACM04NF9oTs1g2ykAAAAALRehGYeUcqAZ2MbMQlW4PeYWAwAAAAAmITTjkBJbh6l1RLCcHq827i0yuxwAAAAAMAWhGYdksViUnEAzMAAAAAAtG6EZNaIZGAAAAICWjtCMGvmbgRGaAQAAALRQhGbUyNcMbMe+EhWUuswtBgAAAABMQGhGjVpFBKtLm3BJ0po9DnOLAQAAAAATEJpxWMkHRptZ1wwAAACgJSI047BY1wwAAACgJSM047BS/KG5QIZhmFsMAAAAADQyQjMOq1/HaNmtFu0rrlBmQbnZ5QAAAABAoyI047BCg2zq3SFKEuuaAQAAALQ8hGYcka8ZGOuaAQAAALQ0hGYcUQrNwAAAAAC0UIRmHJEvNK/NKJDb4zW3GAAAAABoRIRmHFG3tpGKDLGrzOXRttxis8sBAAAAgEZDaMYR2awWDegUI0lKTXOYWwwAAAAANCJCM2olpXOsJGl1hsPUOgAAAACgMRGaUSu/d9AuMLcQAAAAAGhEhGbUiq8Z2JbsIpU63eYWAwAAAACNhNCMWmkfE6p20SHyeA2t21NodjkAAAAA0CgIzag132jzavZrBgAAANBCEJpRa8kHQnMqzcAAAAAAtBCEZtRayoFmYIw0AwAAAGgpCM2otQEJMbJYpIz8Mu0rrjC7HAAAAABocIRm1FpUaJC6t42UxGgzAAAAgJaB0Iw6SaYZGAAAAIAWhNCMOvm9GViBuYUAAAAAQCMgNKNODm4GZhiGucUAAAAAQAMjNKNOeneIUrDdqoIyl3bllZpdDgAAAAA0KEIz6iTIZlX/jtGSWNcMAAAAoPkjNKPO/OuaCc0AAAAAmjlCM+oshdAMAAAAoIUgNKPOfKF5Q2ahnG6vucUAAAAAQAMiNKPOOrcOV2x4kJwerzZlFZpdDgAAAAA0GEIz6sxisSj5wNZTTNEGAAAA0JwRmnFUaAYGAAAAoCUgNOOoDDoQmtl2CgAAAEBzRmjGURmYECNJ2p5bosJyl8nVAAAAAEDDIDTjqLSJDFFi6zBJ0pr0ApOrAQAAAICGQWjGUfM1A1ud4TC1DgAAAABoKIRmHLUUmoEBAAAAaOYIzThqB4dmwzDMLQYAAAAAGgChGUetX8cY2awW5RZVaG9BudnlAAAAAEC9IzTjqIUF29SrXZQktp4CAAAA0DwRmnFMUjrHSpJSaQYGAAAAoBkiNOOYpPg6aDPSDAAAAKAZIjTjmCQfaAa2NqNAHi/NwAAAAAA0L4RmHJPu8ZGKCLapxOnRtpxis8sBAAAAgHpFaMYxsVktGpAQI4kp2gAAAACaH0IzjplvijbNwAAAAAA0N4RmHDNfM7DUNIepdQAAAABAfSM045j5tp3anF2kMqfH3GIAAAAAoB4ddWheuHChLBaLFixYIEmaP3++evbsqYiICE2aNEmlpaX1VSMCXPvoUMVHhcjjNbQ+s8DscgAAAACg3hxVaHa5XLr55pv9XzscDl188cW6++67tX79eu3atUtPPPFEvRWJwGaxWH5f10wzMAAAAADNyFGF5hdeeEHx8fGKiansmjxnzhwlJCToxhtvVFJSku677z598MEH9VooAlsKoRkAAABAM1Tn0JyRkaGnn35ar7zyiv/YokWLNGLECP/Xw4YNU1pamtLT0w95j4qKChUWFlZ5oWnzhebVdNAGAAAA0IzUOTTfcccduuGGG9SnTx//saysLMXFxfm/btOmjSQpOzv7kPd46qmnFBMT438lJibWtQwEGN9ezen7y5RXXGFyNQAAAABQP+oUmufNm6cVK1booYceqvaeYRjV/myxWA55n6lTp6qgoMD/qmlEGk1HdGiQjmsbIUlak0EzMAAAAADNg70uJ8+cOVN79+5Vx44dJUkFBQUaN26cOnTooHbt2vnPy8vLkyS1b9/+kPcJCQlRSEjI0daMAJWcGKvtuSVale7Qyb3jzS4HAAAAAI5ZnUaan3vuOW3evFmpqalKTU1VVFSUZsyYoYceeki//vqr/7wlS5YoKSlJnTp1qveCEbgG+dY10wwMAAAAQDNRp9AcFxenpKQk/8tqtap9+/YaP3689u7dq9dee027du3Sc889p8mTJzdUzQhQyQc1Azt4uj4AAAAANFVHteXUH8XExGjWrFl6/vnn1bdvX3Xt2lVTp06tj1ujCendPlrBNqscpS6l7S81uxwAAAAAOGZ1WtP8Rw6Hw//nM844Q1u3bj3WetCEBdut6tsxWqnpDqWmO9SlTYTZJQEAAADAMamXkWbAx7dfcyrrmgEAAAA0A4Rm1KsUmoEBAAAAaEYIzahXvmZg6zIL5fJ4zS0GAAAAAI4RoRn1KqlNuGLCguR0e7Vpb5HZ5QAAAADAMSE0o15ZLBb/aHNqhsPUWgAAAADgWBGaUe9SEmIksa4ZAAAAQNNHaEa9S6YZGAAAAIBmgtCMeucLzdtyi1VU7jK3GAAAAAA4BoRm1Lu4yBAltAqTYUhrMwrMLgcAAAAAjhqhGQ2CZmAAAAAAmgNCMxpESkKsJNY1AwAAAGjaCM1oEP6RZkIzAAAAgCaM0IwG0b9TtGxWi7ILK5RVUG52OQAAAABwVAjNaBDhwXb1bBclidFmAAAAAE0XoRkNJiUxRpK0mmZgAAAAAJooQjMaTPKBZmCpaQ5T6wAAAACAo0VoRoNJ6RwrSVq7p0Aer2FuMQAAAABwFAjNaDA94qMUHmxTcYVbO3KLzS4HAAAAAOqM0IwGY7Na1L9T5bpmmoEBAAAAaIoIzWhQKezXDAAAAKAJIzSjQflCMx20AQAAADRFhGY0qOQDoXnT3iKVuzzmFgMAAAAAdURoRoPqGBOquMgQub2G1mcWml0OAAAAANQJoRkNymKxKCWRZmAAAAAAmiZCMxqcf10zoRkAAABAE0NoRoNLphkYAAAAgCaK0IwGN7BTrCRpd16p8kuc5hYDAAAAAHVAaEaDiwkPUre4CElSKqPNAAAAAJoQQjMaBeuaAQAAADRFhGY0imRCMwAAAIAmiNCMRvF7M7ACGYZhbjEAAAAAUEuEZjSKPh2iFGyzan+JU+n7y8wuBwAAAABqhdCMRhFit6lPx2hJNAMDAAAA0HQQmtFoUhJiJLGuGQAAAEDTQWhGo6EZGAAAAICmhtCMRuMLzWv3FMjl8ZpbDAAAAADUAqEZjaZrmwhFh9pV4fZqc1aR2eUAAAAAwBERmtForFbLQVtPOUytBQAAAABqg9CMRpWcECtJSk1zmFoHAAAAANQGoRmNipFmAAAAAE0JoRmNKjmxctuprTnFKq5wm1wNAAAAABweoRmNKj4qVJ1iw2QY0tqMArPLAQAAAIDDIjSj0flGm1PZrxkAAABAgCM0o9H5moGtJjQDAAAACHCEZjS6FJqBAQAAAGgiCM1odP07xchqkfYWlCu7sNzscgAAAACgRoRmNLqIELt6touSxLpmAAAAAIGN0AxT+KdoE5oBAAAABDBCM0yRzLpmAAAAAE0AoRmm8HXQXpNeIK/XMLcYAAAAAKgBoRmm6NkuUmFBNhVVuLVjX7HZ5QAAAADAIRGaYQq7zaoBnWIkSanpBSZXAwAAAACHRmiGaZITK0MzzcAAAAAABCpCM0xDMzAAAAAAgY7QDNP4moFt3FuocpfH3GIAAAAA4BAIzTBNQqswxUUGy+UxtGFvodnlAAAAAEA1hGaYxmKx+EebWdcMAAAAIBARmmEq/7pmQjMAAACAAERohql8oTmV0AwAAAAgABGaYarkhMptp3bllcpR6jS5GgAAAACoitAMU8WGB6trXIQkaXVGgcnVAAAAAEBVhGaYzjfazLpmAAAAAIGG0AzTsa4ZAAAAQKAiNMN0KQd10DYMw9xiAAAAAOAghGaYrk+HaAXZLMorcSojv8zscgAAAADAj9AM04UG2dSnQ7QkaXWGw9xiAAAAAOAghGYEhOSEWElSaprD1DoAAAAA4GCEZgQE/7pmRpoBAAAABBBCMwKCr4P22j0Fcnu85hYDAAAAAAcQmhEQusVFKCrErnKXV1uyi80uBwAAAAAkEZoRIKxWiwYmxkhiv2YAAAAAgYPQjIBx8H7NAAAAABAICM0IGL4O2jQDAwAAABAoCM0IGL6R5i3ZRSqpcJtbDAAAAACI0IwAEh8dqg4xofIalV20AQAAAMBshGYEFNY1AwAAAAgkhGYEFN9+zaxrBgAAABAICM0IKP5mYOlMzwYAAABgPkIzAsqAhBhZLNIeR5lyisrNLgcAAABAC0doRkCJDLGrZ3yUJEabAQAAAJiP0IyAk5wYI4lmYAAAAADMR2hGwKEZGAAAAIBAQWhGwPE1A0tNd8jrNcwtBgAAAECLRmhGwOnVPkqhQVYVlbu1M6/E7HIAAAAAtGCEZgScIJtV/TuyrhkAAACA+QjNCEj+dc2EZgAAAAAmIjQjIPlCcyqhGQAAAICJCM0ISIMOhOYNewtV4faYWwwAAACAFovQjICU0CpMrSOC5fIY2ri3yOxyAAAAALRQhGYEJIvFouQEmoEBAAAAMBehGQGLdc0AAAAAzEZoRsBKoYM2AAAAAJMRmhGwkhNiJUk79pWooNRlbjEAAAAAWiRCMwJWq4hgdWkTLklas8dhbjEAAAAAWiRCMwKab7Q5Nc1hah0AAAAAWiZCMwKaf11zhsPUOgAAAAC0TIRmBLTfO2gXyDAMc4sBAAAA0OIQmhHQ+nWMlt1q0b7iCmUWlJtdDgAAAIAWhtCMgBYaZFPvDlGSWNcMAAAAoPERmhHwWNcMAAAAwCyEZgQ8fwftdIepdQAAAABoeQjNCHi+kea1GQVye7zmFgMAAACgRalzaN64caOGDx+uyMhIjRo1Slu3bpUkrVy5UikpKQoLC9MZZ5yhnJycei8WLVO3tpGKDLGrzOXR1pxis8sBAAAA0ILUOTRfcsklOvfcc7Vlyxb17t1bN954o7xery688EKNGzdOW7duVVhYmO66666GqBctkM1q0cCEGEnSaqZoAwAAAGhEdQrN+fn5ioqK0l/+8hd17NhR559/vjZs2KCffvpJ+/fv16OPPqqEhAQ98sgjmjNnjkpKShqqbrQwyTQDAwAAAGCCOoXmVq1a6eeff1ZwcLCcTqdmzZqlQYMGadGiRTrhhBNkt9slSSkpKfJ4PFq5cuUh71NRUaHCwsIqL+Bwfm8GVmBuIQAAAABalKNuBBYeHq65c+fq5ZdfVlZWluLi4n6/qdWqVq1aKTs7+5DXPvXUU4qJifG/EhMTj7YMtBCDOsdKkjZnFarU6Ta3GAAAAAAtxlGH5qVLl2rw4MG6/fbbJUmGYVR53zAMWSyWQ147depUFRQU+F/p6elHWwZaiHbRoWofHSqvIa3bw8wEAAAAAI2jTqE5NzdXq1atkiQNHjxYTz75pL7++mu1bdtWubm5/vM8Ho8cDofat29/yPuEhIQoOjq6ygs4kuREmoEBAAAAaFx1Cs2rVq3S2Wef7f/aN5I8duxYLVu2TG6323+e3W7XoEGD6rFUtHS+ZmCpNAMDAAAA0EjqFJpPOOEElZeX65VXXlFGRoaef/55jRo1SqNGjVLbtm31yCOPKCMjQ4899pguuOAChYeHN1TdaIFSfKE5zWFqHQAAAABajjqF5tjYWM2ePVvTp09Xnz59lJ2drffff19Wq1WffvqpvvrqK3Xv3l3l5eV6/vnnG6pmtFADOsXIYpH2OMqUW1RhdjkAAAAAWgB7XS8YO3asVq9eXe344MGDD3kcqC9RoUHq3jZSW3OKtSbDoVP7tDO7JAAAAADN3FF3zwbM4F/XTDMwAAAAAI2A0IwmJYXQDAAAAKAREZrRpPhC8+p0R7W9wQEAAACgvhGa0aT0ah+lYLtVheVu7corNbscAAAAAM0coRlNSpDNqv4doyVJqen5JlcDAAAAoLkjNKPJSUlsJUlanV5gciUAAAAAmjtCM5qc5MQYSTQDAwAAANDwCM1ocnzNwDZkFsrp9ppbDAAAAIBmjdCMJqdz63C1Cg+S0+PVxr2FZpcDAAAAoBkjNKPJsVgsSvZtPZXhMLUWAAAAAM0boRlNUnJCrCTWNQMAAABoWIRmNEm+dc2rCc0AAAAAGhChGU3SwITKDtrbc0tUUOYyuRoAAAAAzRWhGU1Sm8gQdW4dLklam8F+zQAAAAAaBqEZTRbNwAAAAAA0NEIzmqzkA1O0aQYGAAAAoKEQmtFk+ZqBpaY7ZBiGucUAAAAAaJYIzWiy+neKkc1qUW5RhfYWlJtdDgAAAIBmiNCMJis0yKbe7aMksfUUAAAAgIZBaEaT5msGlkozMAAAAAANgNCMJi0lIVaSlJrmMLUOAAAAAM0ToRlNWkrnWEnS2j0F8nhpBgYAAACgfhGa0aQd1zZSEcE2lTo92pZTbHY5AAAAAJoZQjOaNJvVogEH9mumGRgAAACA+kZoRpPnawa2itAMAAAAoJ4RmtHkDToQmhlpBgAAAFDfCM1o8nwjzZuzi1Tm9JhbDAAAAIBmhdCMJq99dKjio0Lk8Rpan1lgdjkAAAAAmhFCM5o8i8XiH21OZYo2AAAAgHpEaEazkEJoBgAAANAACM1oFnyheXWGw9Q6AAAAADQvhGY0C769mtP3lymvuMLkagAAAAA0F4RmNAvRoUE6rm2EJEabAQAAANQfQjOajZTEVpKk1HQ6aAMAAACoH4RmNBspiZVTtFfTDAwAAABAPSE0o9lIPqgZmGEY5hYDAAAAoFkgNKPZ6N0+WsF2qxylLu3OKzW7HAAAAADNAKEZzUaw3ap+HaMl0QwMAAAAQP0gNKNZSU6IlSSlsq4ZAAAAQD0gNKNZSfGtayY0AwAAAKgHhGY0K75mYOsyC+V0e80tBgAAAECTR2hGs5LUJlwxYUFyur3anFVkdjkAAAAAmjhCM5oVi8XiH21OpRkYAAAAgGNEaEazk5IQI4l1zQAAAACOHaEZzY5/pJnQDAAAAOAYEZrR7PhC8/bcYhWWu8wtBgAAAECTRmhGsxMXGaKEVmEyDGldRoHZ5QAAAABowgjNaJZoBgYAAACgPhCa0SylJMRKklLTHKbWAQAAAKBpIzSjWUrpHCtJWs1IMwAAAIBjQGhGs9SvY7RsVouyCyuUVVBudjkAAAAAmihCM5ql8GC7eraLksTWUwAAAACOHqEZzVYK+zUDAAAAOEaEZjRbKYkxkqTVhGYAAAAAR4nQjGbLt+3U2j0F8ngNc4sBAAAA0CQRmtFs9YiPUniwTcUVbu3ILTa7HAAAAABNEKEZzZbNatGATpVTtFcxRRsAAADAUSA0o1nzNQNjXTMAAACAo0FoRrPmW9e8OsNhah0AAAAAmiZCM5o1X2jetLdI5S6PucUAAAAAaHIIzWjWOsaEqm1UiNxeQ+szC8wuBwAAAEATQ2hGs2axWJScECtJSk0nNAMAAACoG0Izmr2UxMoO2jQDAwAAAFBXhGY0ezQDAwAAAHC0CM1o9gYemJ69O69U+0uc5hYDAAAAoEkhNKPZiwkLUre2EZIYbQYAAABQN4RmtAgpB0abWdcMAAAAoC4IzWgR/OuaCc0AAAAA6oDQjBYh5UBoTk13yDAMc4sBAAAA0GQQmtEi9O4QpWCbVfmlLqXvLzO7HAAAAABNBKEZLUKI3aY+HaMlSak0AwMAAABQS4RmtBgpCTGSWNcMAAAAoPYIzWgxUjrHSqpc1wwAAAAAtUFoRouRfGDbqXV7CuTyeM0tBgAAAECTQGhGi5HUJkLRoXZVuL3anFVkdjkAAAAAmgBCM1oMq9Xi36+ZKdoAAAAAaoPQjBbFt18zzcAAAAAA1AahGS2Kb13zaradAgAAAFALhGa0KAMTK7ed2ppTrOIKt8nVAAAAAAh0hGa0KPFRoeoUGybDkNYw2gwAAADgCAjNaHF+X9dcYG4hAAAAAAIeoRktTvKBKdo0AwMAAABwJIRmtDg0AwMAAABQW4RmtDj9O8XIapH2FpQru7Dc7HIAAAAABDBCM1qciBC7eraLkiSlMkUbAAAAwGEQmtEi/d4MzGFqHQAAAAACG6EZLVKyLzSzrhkAAADAYRCa0SL5moGtSS+Q12uYWwwAAACAgEVoRovUs12kwoJsKqpwa8e+YrPLAQAAABCgCM1okew2qwZ0qtyvOTW9wORqAAAAAAQqQjNarOTEytBMMzAAAAAANSE0o8XyNQNj2ykAAAAANSE0o8XybTu1cW+hyl0ec4sBAAAAEJAIzWixOsWGKS4yWG6voQ17C80uBwAAAEAAIjSjxbJYLP6tp1jXDAAAAOBQCM1o0VjXDAAAAOBwCM1o0XzrmhlpBgAAAHAohGa0aAMTKred2pVXKkep0+RqAAAAAAQaQjNatNjwYHWNi5Akrc4oMLkaAAAAAIGG0IwWL/nAaHNqmsPcQgAAAAAEHEIzWjz/uuYMh6l1AAAAAAg8dQ7NO3bs0JgxYxQVFaWxY8dq9+7dkqT58+erZ8+eioiI0KRJk1RaWlrvxQINIfmgZmCGYZhbDAAAAICAUufQfP3116tz585at26d2rRpo1tuuUUOh0MXX3yx7r77bq1fv167du3SE0880RD1AvWuT4doBdksyitxKiO/zOxyAAAAAASQOoVmp9OpH374QVOnTlWXLl10zTXX6Oeff9acOXOUkJCgG2+8UUlJSbrvvvv0wQcfNFTNQL0KDbKpT4doSezXDAAAAKCqOoVml8ulZ599Vl27dpUk5eXlKSwsTIsWLdKIESP85w0bNkxpaWlKT08/5H0qKipUWFhY5QWYif2aq3N5vHrg8zW64f3lKnW6zS4HAAAAMEWdQnNERITuuecehYWFyeVy6cUXX9Tll1+urKwsxcXF+c9r06aNJCk7O/uQ93nqqacUExPjfyUmJh7DtwAcu+SEWEk0AzvY419t0CfL0jV/fbaenbfZ7HIAAAAAUxxV92y3261LLrlENptNjz32mCRVaaDk+7PFYjnk9VOnTlVBQYH/VdOINNBYfM3A1u4pkNvjNbeYAPDx0jS9t3i3/+t3f92lJTvyTKwIAAAAMEedQ7PX69XEiRO1a9cuzZs3T2FhYerQoYNyc3P95+TlVf7lun379oe8R0hIiKKjo6u8ADN1i4tQVKhd5S6vNmcXmV2OqZbt2q+H/7tOkvSX03vqkhM6S5Lu/Wy1SiqYpg0AAICWpc6h+aGHHtL27dv1/fffq1WrVpKkUaNG6ddff/Wfs2TJEiUlJalTp071VynQgKxWy+9TtNMLzC3GRHscZbrx/RVyeQydPaCDbj2lux48u486xYYpfX+Znpq70ewSAQAAgEZVp9C8e/duPf/883rttddkGIYcDoccDofGjx+vvXv36rXXXtOuXbv03HPPafLkyQ1VM9AgkhNjJLXcZmBlTo+uf2+58kqc6tshWs9NGCiLxaLIELuevWigJOmDJWn6Zes+kysFAAAAGk+dQvOCBQtUXl6uESNGqFWrVv5Xfn6+Zs2apeeff159+/ZV165dNXXq1IaqGWgQLbkZmGEYuvez1VqfWag2EcGafsUQhQfb/e+f1D1Ol5/YRZJ0/+drVFTuMqtUAAAAoFFZjIM7eJmksLBQMTExKigoYH0zTJNTWK4TnvxeVou09tE/KSLEfuSLmolXftym5+Zvlt1q0UfXnagTuraudk5JhVtnvrhQ6fvLdMkJiXrqgoEmVAoAAADUj9rm0KPqng00R/HRoeoYEyqvUdlFu6X434Zs/ePbyi2l/j6+3yEDsyRFhNj13EXJkqSPl6brpy25hzwPAAAAaE4IzcBBfFtPtZR1zVuzi3TnzFQZhjT5xM66bFiXw55/Yrc2uuqkJEnS/Z+tUUEZ07QBAADQvBGagYP4Q3MLWNfsKHXq2veWq7jCrWFdW+uRc/rV6rr7/tRbSW3ClVVYrse/2tDAVQIAAADmajmLNoFaSDkQmlPTHKbW0dDcHq9u/WiVdueVqlNsmF69bLCCbLX7DC0s2KZ/TEjWhDcW67MVGSoqdynYbmvgihtPkM2ia0d2U9+O9FcAAAAAoRmoYkCnGFktUmZBuXIKyxUfHWp2SQ3iyW826Zdt+xQebNOMK4eqTWRIna4fmtRa147sqjd/3qn567MbqErzOEpdenvK8WaXAQAAgABAaAYOEhFiV4/4KG3OLtLqjAKd3rf5heZPl6fr7UU7JUnPX5ysPh2ObkT1vjN7q2e7KBWVu+uzPFPtK67Qqwu2a2VavrxeQ1arxeySAAAAYDJCM/AHyYkxlaE53aHT+7Yzu5x6tWJ3vh6cs06SdMepPXRm/w5Hfa8gm1UThibWV2kBweXx6u1FO+UodWnHvmJ1j48yuyQAAACYjEZgwB+kJLaSJKU2sw7aWQXluvGDFXJ6vPpTv3a649QeZpcUcIJsViUnxEqq/IABAAAAIDQDf5CcGCOpsoO212uYXE39KHd5dP37y5VbVKHe7aP0/MUpTD2uwZAulR+aEJoBAAAgEZqBanq2i1JokFVF5W7tzCsxu5xjZhiG7v98jdZkFKhVeJDevGKoIkJYmVETQjMAAAAORmgG/iDIZlX/jgdGm5vBFO03Fu7Qf1MzZbNa9Mplg5XYOtzskgLaoM6VoXl7bonyS5wmVwMAAACzEZqBQ/Dv19zEQ/OPm3L0zLxNkqRHzumrEcfFmVxR4GsdEaxubSMkSavSGW0GAABo6QjNwCEkHwjNTXmkeVtOsW7/eJUMQ7rkhERdfmIXs0tqMoZ0Zoo2AAAAKhGagUPwjTRv2FuoCrfH3GKOQkGZS9e/t1xFFW4dn9RKfz+3vywWGn/Vlm9d8/JdhGYAAICWjm5AwCEktApT64hg7S9xauPeIn+Ibgo8XkO3f7xKO/aVqGNMqF6bPETBdj4fqwtfaF6d4ZDL41WQrXn+/LZkFwXMBwN2m0Wn9o5Xm8gQs0sBAACogtAMHILFYlFKYqx+2JSj1LT8JhWan5m3ST9tyVVokFXTrxiqOEJInR3XNlIxYUEqKHNp495CDTywd3Nz4nR7NfGNxcovdZldit+4gR308qWDzS4DAACgCkIzUIPkhMrQvDqjwOxSam32ygxNX7hDkvTcRcnq3ynG5IqaJqvVosGdY/Xj5lyt2J3fLEPzyrR85Ze6FBli1/Dj2phaS0GpS0t37dfGvYWm1gEAAHAohGagBsmJTWvbqdR0hx6YvVaSdMvJx+mc5I4mV9S0DenSyh+arzqpq9nl1LuFW3IlSaf1idc/Jw0ytZa0vFKNfu5HpeeXyes1ZLWy/h4AAASO5rlQD6gHyQdGF3fsK1FBAE1hPZScwnLd8P5yOd1endYnXn85vZfZJTV5gw+sa17ZTDto/3QgNI/u2dbkSqSOsaGyWS1yur3KLio3uxwAAIAqCM1ADVpFBCupTbikyoZQgarc5dH1769QdmGFesRH6oWJKYzU1YPkhFjZrBZlFpQr01Fmdjn1KreoQuszK6dCj+phfmi226zqFBsmqXLUGQAAIJAQmoHDCPT9mg3D0INz1ik13aGYsCC9ecVQRYUGmV1WsxARYlefDlGSmt9+zb9sqxxl7tcxWm2jAqNRXJcDH1Dt3k9oBgAAgYXQDByGb4p2oI40v/XLTn2+MkNWi/TypYOUFBdhdknNypDOlVO0m1to/mlz4EzN9klsXRma0wnNAAAgwBCagcPwjTSnphfIMAxzi/mDhVty9eQ3GyVJD57dNyCm2TY3Q5JaS6rsNN1ceL2Gft66T5I0JoBCc+cDoXk307MBAECAITQDh9GvY7TsVov2FVdoTwCta925r0S3frRSXkO6aEiCrj4pyeySmqUhB5qBrc8sVKnTbXI19WPD3kLllTgVEWzT4AMj6YGgy4HQnMZIMwAACDCEZuAwQoNs6tMhWpK0Oj0w9msuKnfpuveWq7DcrcGdY/XE+f1lsdD4qyF0jAlV++hQebyG1jSh/boPx9c1e/hxcQq2B87/BTA9GwAABKrA+RsTEKD8+zUHwLpmj9fQnZ+kaltOsdpHh+r1y4coxG4zu6xmy2Kx+Eebm8u6Zl9oHtMrcKZmS1LnA43A8kqcKq5oHqP6AACgeSA0A0fgawaWGgAdtKd9u1nfb8pRiN2q6VcMUXxUqNklNXvNab/monKX//sYE2Br4KNDg9QqvLLzO9tOAQCAQEJoBo5gUOdYSdLajAK5PV7T6vhidaZeXbBdkvTsRQM18ECYR8PyjzSn5QdcM7i6Wrw9T26voaQ24f6R3UDSuU1l9/e0/SUmVwIAAPA7QjNwBN3iIhUZYleZy6OtOcWm1LBuT4Hu+2y1JOmGMd00PqWTKXW0RH07RCvEbpWj1KXtuU07zPmnZgdQ1+yDdaYZGAAACECEZuAIrFaLBiYcWNdswhTt3KIKXffecpW7vDq5V1vd96fejV5DSxZst/qn6DflKdqGYWjh1sDbn/lgdNAGAACBiNAM1IJvv+bGbgZW4fbopg9WaG9Bubq1jdCLlwySzUqn7MY2JKnpNwPblVeq9P1lCrJZdGK3NmaXc0js1QwAAAIRoRmohZQDoXlVmqPRnmkYhh7573ot352vqFC7ZlwxVNGhQY32fPxuSOff1zU3VT9tzpEkHZ/UWhEhdpOrOTS2nQIAAIGI0AzUgi80b8kuUqmzcbbDeW/xbn2yLF1Wi/TSJYPUrW1kozwX1fk6aG/LKZaj1GlyNUdn4dZ9kgJ3arYkdTnQnCwjv8zUpnsAAAAHIzQDtdAuOlTto0PlNaR1ewob/Hm/btunx77aIEl64M+9NbZXfIM/EzVrHRGsbnGVnZ0bc7ZBfalwe7R4e54kaXSAbTV1sHbRoQq2WeX2GtpbUG52OQAAAJIIzUCtJSdWNgNLTW/YKbppeaW6+aOV8ngNnT+ok64b1a1Bn4fa8Y02N8V1zct35avM5VHbqBD16RBldjk1slktSmgdJolmYAAAIHAQmoFaSkmsDE2r0wsa7BnFFW5d995yOUpdSk6I0VMXDJDFQuOvQODbr3n57v0mV1J3Cw9sNTW6R9uA/31i2ykAABBoCM1ALf0+0uxokPt7vYbumpmqzdlFio8K0RuXD1VokK1BnoW684Xm1ekFcjWx9ba+/ZlH94wzuZIjY9spAAAQaAjNQC0N6BQji0Xa4yhTblFFvd//n//bou82ZCvYZtXrlw9R+5jQen8Gjl73tpGKDrWrzOXRpr1FZpdTa9mF5dqUVSSLRRoVwOuZfXwdtNPYdgoAAAQIQjNQS1GhQep+oIP16noebf56zV7964dtkqQnLxigwQe2OELgsFotB61rbjpTtH1Tswd2ilHriGCTqzmyLm0qG64x0gwAAAIFoRmoA9/WU6szHPV2z/WZBbrn09WSpGtGdtVFQxLq7d6oX7/v1+wwt5A6aApbTR3Mt6Z5d16JyZUAAABUIjQDdZB8IDTX17rmvOIKXf/eCpW5PBrVI05T/9y7Xu6LhuFb17yyiXTQ9ngN/by1cqR5TBMLzYXlbhWUukyuBgAAgNAM1Il/pDndIcMwjuleTrdXN324UnscZUpqE66XLxksu41/JQNZcmKsrAfWte8tKDO7nCNau6dAjlKXokLt/t/dQBcWbFPbqBBJTNEGAACBgb+hA3XQq32UQuxWFZa7tXPfsU0f/fuX67V0535Fhtg148qhigkPqqcq0VAiQuzq0yFaUtPYr9m3nvmk4+Ka1Acy/ina+5miDQAAzNd0/hYFBIAgm1X9O1VuPXUs65o/WLJbH/6WJotFenFSirrHR9VThWhoQ/zNwAI/NPu2mhrTq2lMzfZh2ykAABBICM1AHSUnxEqq3K/3aCzZkadHv1gvSbr3T710ap929VUaGkFTWddcUObyr71vKk3AfNh2CgAABBJCM1BHyYmVI81H0wwsfX+pbv5wpdxeQ+cmd9RNY46r5+rQ0HyheX1mocqcHpOrqdmv2/bJ4zV0XNsIdYoNM7ucOunShpFmAAAQOAjNQB35GiptyCxUhbv2oanU6dZ17y3X/hKn+neK1jMXDpTFYmmgKtFQOsWGqV10iNxeQ2vqceux+uabmt3URpmlg7edIjQDAADzEZqBOurcOlytwoPk9Hi1aW9Rra4xDEP3fLpam7KKFBcZoumXD1VYsK2BK0VDsFgsv69rTgvMKdqGYfibgDWVraYO1vnASPPegjI53V6TqwEAAC0doRmoI4vF4t+vubbNwF76YZu+WZulIJtFr08erI5NbLosqhrcObDXNW/PLVZmQbmC7VYN69rG7HLqrG1kiMKCbPIaUqYj8Lf2AgAAzRuhGTgKvmZgtVnXPH99lp7/bosk6f/O66+hSa0bsDI0hoM7aB/rft0N4act+yRJw7q2bpIzGiwWy0HbTjFFGwAAmIvQDBwF37rmI4XmzVlFuntmqiRpyogkTTy+c8MWhkbRr2OMgu1W5Ze6tOMY9+tuCD814anZPolsOwUAAAIEoRk4Cr7p2TtyS1RQ5jrkOfklTl373jKVOD0acVwbPXh2n0asEA0p2G5VckJlF/VA26+53OXRbzvyJDXNJmA+nf3bTgXehxIAAKBlITQDR6F1RLD/L/VrM6rv1+zyeHXLRyuVvr9MnVuH65VLByvIxr9uzcmQLpXT7ANtXfPSnftV4faqfXSoesRHml3OUWPbKQAAECj4WzxwlA7XDOyJrzfq1+15igi26c0rhqpVRHDjFocGd/C65kBy8NTsprylGdtOAQCAQEFoBo6Sb13zqjRHleMzl6Xp3V93SZJemJiiXu2jGrcwNIrBnWMlSVtzilVQeugp+mZY2IT3Zz6Yb9up9P2lAdlsDQAAtByEZuAopSRWrmlNTXf4/1K/fNd+/e0/6yRJd5/eU2f0a29afWhYbSJD1DUuQpK0Mj0wRpszHWXamlMsq0Ua2T3O7HKOSUKrMFksUonTo/0lTrPLAQAALRihGThK/TrGyGa1aF9xhfYWlCvTUaYbP1ghl8fQWQPa67ZTuptdIhpYoO3X7BtlTkmMVUx4kMnVHJsQu00dokMlse0UAAAwF6EZOEqhQTb1PjD1esmOPF3//nLtK3aqT4do/WNCcpNeT4ra8a1rXr4rQELz1uYxNdvHt+1UOqEZAACYiNAMHAPfuuaH/rNO6/YUqnVEsN68YojCg+3mFoZG4QvNqekOuT1eU2txe7z6Zes+Sc0nNPs6aNMMDAAAmInQDBwDXwftEqdHdqtFr102WAmtws0tCo2mR3ykokLtKnN5tCmryNRaVmc4VFjuVkxYkJITYk2tpb7492pmpBkAAJiI0Awcg0EHQrMkPXpuPw3r1sa8YtDorFaLf12z2VtP/bSlcpR5ZI842azNY2lAIqEZAAAEAEIzcAy6x0fqL6f31CPn9NXkE7uYXQ5MECj7NfuagI3p0TymZktSlzaV3cnTmJ4NAABMxMJL4BhYLBbddmoPs8uAiQIhNOeXOLU6wyGp+axnln6fnp1VWK5yl0ehQTaTKwIAAC0RI80AcAySE2NltUh7HGXKKig3pYZftu2TYUi92kWpfUyoKTU0hFbhQYoKqfxsNyOf0WYAAGAOQjMAHIPIELt6t4+WZN5os29q9uiecaY8v6FYLBbWNQMAANMRmgHgGJk5RdswDP/+zGN6xjf68xsa204BAACzEZoB4Bj5Q3Na44fmzdlFyi6sUGiQVUOTWjX68xsa204BAACzEZoB4Bj5QvP6PQUqd3ka9dm+qdkndmvTLBtldT4w0pxOaAYAACYhNAPAMUpoFab4qBC5vYbWZBQ06rN/8m011Yy6Zh/MN9LM9GwAAGAWQjMAHCOLxWLKuuZSp1vLdlY+rzltNXWwg6dnG4ZhcjUAAKAlIjQDQD0wIzT/tmO/nB6vOsWGqVtcRKM9tzF1jA2TzWpRhdurnKIKs8sBAAAtEKEZAOrB4AOheWVafqONiPqnZvdqK4vF0ijPbGxBNqs6xlbuPf3dhmyTqwEAAC0RoRkA6kG/jtEKtlu1v8SpnftKGuWZ/v2ZezTPqdk+Zw/oKEl66L/r9P7iXeYWAwAAWhxCMwDUgxC7TQM7xUhqnCna6ftLtWNfiWxWi0Z0b9PgzzPTfX/qpSuGd5FhSA/9d71e+n4r65sBAECjITQDQD0ZctAU7Ya2cGvlKPOQzq0UHRrU4M8zk9Vq0d/P7afbT+kuSZr23Rb939cb5fUSnAEAQMMjNANAPWnMZmA/bT4wNbtnXIM/KxBYLBbdfUYvPTSuryTprV926r7P18jt8ZpcGQAAaO4IzQBQT3zNwLZkF6ugzNVgz3F5vPp1e56k5rvVVE2uGdlV/5iQLJvVos9WZOiWj1aq3OUxuywAANCMEZoBoJ7ERYYoqU3lvsKrGnCK9qo0h4or3GodEaz+HWMa7DmB6qIhCXr1ssEKtlk1f322rn53mYor3GaXBQAAmilCMwDUI//WUw04RfunLTmSpFE94mS1Ns+tpo7kT/3a692rjldEsE2/bs/TZW8uUX6J0+yyAABAM0RoBoB65FvXvLwBQ/PCLfskNf+tpo5kRPc4fXTdiWoVHqTVGQW6+I3FyiooN7ssAADQzBCaAaAe+UJzarqjQZpU7Suu0No9BZKkUS2kCdjhJCfGatYNw9U+OlRbc4p14Wu/alcj7ZMNAABaBkIzANSjHvFRigqxq9Tp0aasonq//y9bK0eZ+3aIVnxUaL3fvynq0S5Kn900XEltwrXHUaaLXl+sDZmFZpcFAACaCUIzANQjm9WiQQ24X/PCLb6tplr21Ow/SmgVrk9vHKG+HaK1r7hCE6cv1vJd+80uCwAANAOEZgCoZ0M6N8x+zV6voYUHRppbyv7MddE2KkQfX3+ijk9qpaJytya/9ZsWbM4xuywAANDEEZoBoJ751jXXd2jesLdQ+4orFB5s09Aurev13s1FTFiQ3rt6mMb2aqtyl1fX/nu5vlydaXZZAACgCSM0A0A9S06MkdUiZeSXKbuw/ro5L9xaOTV7xHFtFGznP981CQu2afrlQ3VOcke5vYZu/2SVPvxtt9llAQCAJoq/dQFAPYsKDVKv9tGS6ne0mfXMtRdst+qfE1M0+cTOMgzpwTnr9MqP22QYhtmlAQCAJobQDAANYEiXWEn1F5qLK9xavqvyXmMIzbVis1r0+Pj+uvXk7pKk5+Zv1tNzNxGcAQBAnRCaAaAB1Pe65sXb8+T2GurSJlxd2kTUyz1bAovFonv+1EsPntVHkvTGwh164PO18ngJzgAAoHYIzQDQAIZ0rmzUtT6zQOUuzzHfzz81uwejzEfjutHd9OyFA2W1SDOXp+vWj1aqwn3s/1wAAEDzR2gGgAaQ2DpMbaNC5PIYWrun4Jjv99OB0MzU7KN38fGJevWywQq2WTV3XZau/fdylVS4zS4LAAAEOEIzADQAi8VSb/s179pXorT9pQqyWTT8uDb1UV6LdWb/Dnp7yvEKD7bp5637dNmM3+QodZpdFgAACGCEZgBoIPW1rtm31dSQLq0UEWI/5rpaupE94vThtcMUExak1HSHJr6xpF63BgMAAM0LoRkAGsjgA6F55e78Y+rY/NNm39Ts+HqpC9Kgzq306Y3D1S46RJuzi3TR679qd16J2WUBAIAARGgGgAbSv1O0gm1W5ZU4tSuv9Kju4XR7tXhHniRpdM+4+iyvxevZLkqf3ThCXdqEK31/mS56fbE2ZRWaXRYAAAgwhGYAaCAhdpsGJMRIOvop2st371ep06O4yBD1aR9dn+VBUmLrcH1643D1bh+l3KIKXfz64nrbJgwAADQPhGYAaEDHuq7Z1zV7dM84Wa2WeqsLv4uPCtXM64drSJdWKix3a/KM3/xbfAEAABCaAaABDTloXfPRWLhlnyS2mmpoMeFBev+aEzS6Z1uVuTy65t/L9PWavWaXBQAAAgChGQAa0OAD205tySlSQZmrTtfmFJZr495CWSzSyO6sZ25o4cF2zbhiqM4e2EEuj6HbPl6pj5emmV0WAAAwGaEZABpQ26gQdWkTLsOQUtMddbp24dbKUeYBnWLUJjKkAarDHwXbrfrXpEG65ITO8hrS1Nlr9fpP280uCwAAmIjQDAANbEjno1vX7FtXO7oHU7Mbk81q0ZPn99dNY4+TJD09d5OenrvpmLYNAwAATRehGQAa2GB/M7D9tb7G6zX0y7bKkebRrGdudBaLRfef2VtT/9xbkvT6T9v11znr5PESnAEAaGmOKjTv3btXY8aMUWpqqv/Y/Pnz1bNnT0VERGjSpEkqLT26PUkBoLnxNQNLTXPI7fHW6pp1mQXaX+JUVIhdgzrHNmB1OJwbxhynpy8YIKtF+nhpmm7/eJWc7tr9MwQAAM1DnUPzDTfcoI4dO2rhwoX+Yw6HQxdffLHuvvturV+/Xrt27dITTzxRr4UCQFPVs12UIkPsKnF6tDm7qFbX/LS5cmr2iO5tFGRjUpCZJp3QWS9fOlhBNou+XrtX1763XKVOt9llAQCARlLnv4k98cQT2rlzZ5Vjc+bMUUJCgm688UYlJSXpvvvu0wcffFBvRQJAU2azWvyjxbXdemrhVt/+zEzNDgRnDeigt6ccr7AgmxZuydXkGb+poLRu3dABAEDTVOfQHBcXp6SkpCrHFi1apBEjRvi/HjZsmNLS0pSenn7Ie1RUVKiwsLDKCwCasyFdat8MrLDcpZVpDkk0AQsko3q01QfXDlNMWJBWpjk0cfpi5RSWm10WAABoYPUy5y8rK0txcb/vIdqmTRtJUnZ29iHPf+qppxQTE+N/JSYm1kcZABCw/KE57cih+ddt++TxGurWNkKJrcMbujTUwZAurTTzhhPVNipEm7KKNOGNxUrfTw8PAACas3pbKHfwVhy+P1sslkOeO3XqVBUUFPhfNY1IA0BzkZIYK4tFSt9fdsTRyZ+2HOiazShzQOrdPlqf3zhCnVuHa3deqS587VdtzqrdWnUAAND01Eto7tChg3Jzc/1f5+XlSZLat29/yPNDQkIUHR1d5QUAzVlUaJB6tYuSdPgp2oZh+PdnHsN65oDVuU24PrtxuHq1i1JOUYUufmOxVtViFgEAAGh66iU0jxo1Sr/++qv/6yVLligpKUmdOnWqj9sDQLNQm3XN23NLtMdRpmC7VcO6tW6s0nAU4qNDNfOGEzWoc6wKyly6bMZv+mXrPrPLAgAA9axeQvP48eO1d+9evfbaa9q1a5eee+45TZ48uT5uDQDNRm3WNftGmU9Iaq3wYHuj1IWjFxserA+vHaZRPeJU6vTo6neXad66vWaXBQAA6lG9hOaYmBjNmjVLzz//vPr27auuXbtq6tSp9XFrAGg2fKF53Z4Clbs8hzzn962m4g75PgJPeLBdM64cqrMGtJfT49XNH67UrGX06gAAoLk46mGMgxt/SdIZZ5yhrVu3HnNBANBcdW4drrjIEO0rrtC6PQUamlR1+nW5y6MlOyp7QozpGW9GiThKIXabXrpksKJC1mrm8nTd9/kaFZS5dN3obmaXBgAAjlG9dc8GAByexWLRkC6xkg69rnnZrv0qd3nVPjpUPdtFNnJ1OFY2q0VPXzhANxwIyk98s1HPzd9U7UNmAADQtBCaAaARHa4ZmG8986gecTVu2YfAZrFYNPWsPrr/zN6SpFd+3K6//WedPF6CMwAATRWhGQAakS80r0zLrzYC+ZNvq6lebDXV1N009jg9ef4AWSzSh7+l6c6ZqXK6vWaXhTpye7wqrnCbXQYAwGS0ZgWARtSvY4yCbVbtK3Zqd16pkuIiJEl7C8q0JbtYVos0sjtNwJqDS4d1VlSoXXfPStWXqzNVVO7Sa5cNUViwzezSUAtuj1eXzvhNS3fuV7e2ERrSuZWGdKl8Hdc2UlYrs0EAoKUgNANAIwoNsql/p2itTHNoxe58f2j+eUvl/r4DE2IVGx5sZomoR+ckd1RUqF03frBCCzbn6vK3ftNbU45XTFiQ2aXhCN5YuENLd+6XJO3ILdGO3BJ9uiJDkhQdatfgLq38QTo5MVYRIfyVCgCaK/4LDwCNbEiXVpWhOS1fFw5JkHTQ1OyeTM1ubsb2itcH1wzT1e8u0/Ld+Zo0fYneu/oEtY0KMbs01GBTVqH++b8tkqTHx/dTp1ZhWrE7Xyt252t1eoEKy91asDlXCzZX/ntrtUh9OkT7R6IHd26lhFZh9CYAgGaC0AwAjWxIl1Z68+edWnmgGZjHa+iXbZUjzaMJzc3S0KTWmnnDcF3+1lJt3FuoCa//qvevGabE1uFml4Y/cHm8+sus1XJ5DJ3Wp50mn9hFFotFp/RuJ6ly2vamrCJ/iF6xO197HGVan1mo9ZmFem/xbklS26gQ/0j04C6t1L9TtELsTM0HgKaI0AwAjWzwgWZgm7OLVFju0racYhWUuRQdaldyQozJ1aGh9OkQrc9uHK7Jb/2mXXmlmvD6Yr1/zQnq0S7K7NJwkFd/3K71mYWKDQ/Skxf0rzZabLdZ1b9TjPp3itGVI5IkSVkF5VqZ9nuIXp9ZoNyiCs1bn6V567MkScE2qwYkxPhHogd3iVV8VGhjf3sAgKNAaAaARhYfFarOrcOVtr9UqQfWNkvSqB5tZbexqUFzlhQXoc9uHKHL3/pNW3OKNeGNxfr3VScoOTHW7NIgaX1mgV76Yask6e/n9qt1qG0fE6qzBnTQWQM6SJLKXR6t3VPgD9Erd+crr8Tp/9qnc+tw/0j0kM6t1Kt9lGw0GAOAgENoBgATDOnSSmn7S7Vid74Wbq1cFzm6J12zW4L2MaGadcNwTXl3mVanO3Tpm0v05hVDNYKu6aZyuiunZbu9hs7s117nJnc86nuFBtl0fFJrHZ/UWpJkGIZ255VWGY3enF2ktP2lSttfqjmr9kiSIoJtSukcqyGdK4P0oM6taBoHAAHAYvxxo1ATFBYWKiYmRgUFBYqOjja7HABocO8v2a2H/rNOAzrFaH1mgbyGtHjqKeoQE2Z2aWgkJRVuXf/+ci3alqdgm1UvXTpIf+rX3uyyWqxp327WSz9sU+uIYH1712jFRTZso7bCcpdWpzv8ITo1zaGiP+wJbbFIPeIj/VO6h3Rppa5xETQYA4B6UtscSmgGABNsyCzUWf/62f91z3aR+vauMSZWBDNUuD264+NUzVufJatFevaiZF10oKM6Gs+aDIfOf/VXebyGXrl0sM4e2KHRa/B4DW3NKaoypXtXXmm181qFB/mndA/u3ErJCbHs/Q0AR6m2OZTp2QBggl7toxQRbFOJ0yNJGt2DrtktUYjdppcvHaSps9fq0xUZuufT1Sooc+makV3NLq3FqHB79JdZq+XxGho3sIMpgVmSbFaLerePVu/20bpsWBdJ0r7iCq3cna+VaQ6t3J2v1RkO5Ze69L+NOfrfxhxJkt1qUd+O0f6R6CFdWqljLDNWAKA+EZoBwAQ2q0WDOrdiqynIbrPq2YsGKjY8SG/+vFOPf7VBBaVO3XV6T6bhNoJ//m+rtuYUKy4yWI+N7292OVXERYbojH7tdcaBaftOt1cb9hb6R6KX796v7MIKrcko0JqMAr376y5JUoeYUH9zsSFdWqlvx2gF0WQQAI4a07MBwCQvfLdFL36/VaFBVqU+fIZCg5hi2ZIZhqFXF2zXc/M3S5ImDEnQo+f2U0QIn283lFVp+brwtV/lNaTXJw/Rmf2b1ppywzCUWVDuD9Erdudrw95CebxV/2oXGmTVwITYypHoA03GWkcEm1Q1AAQOpmcDQIA7vW87vfzjNp3VvwOBGbJYLLrl5O6KDgvSw/9dp09XZGjZrv16fmKKBnduZXZ5zU65y6N7Pl0tryGdl9KxyQVmqfJ3plNsmDrFhvm7fZc63VqdXuDv1L0yLV+OUpeW7tyvpTv3+6/tGhdRZUp3j/hIWdnuCgAOiZFmADBRTlG5YsKCFGInNON3v27bp798ulp7C8pltUi3nNxdt5/agym29ejJbzZq+sIdio8K0bd3jVZsePMceTUMQzv2lVQZjd6aU1ztvKhQuwZ1/n1Kd0rnWEUyywFAM0f3bAAAmrCCMpce/WK9fw/f/p2i9c+JKeoeH2VyZU3f8l37NeGNxTIM6a0rh+rUPu3MLqlRFZS6tDL99xCdmu5Q6YGmhD5Wi9SrfbSGdPFN626txNZhrLMH0KwQmgEAaAa+WpOpB+esU0GZSyF2qx74c29dOTyJqbRHqczp0Z9fXKhdeaW6aEiC/jEh2eySTOf2eLUpq8g/pXvF7nxl5JdVOy8uMrjKlO7+nWJYWgKgSSM0AwDQTGQXluvez9Zo4ZZcSdJJ3dvoHxOS1SGGrYXq6u9frtc7i3apfXSo5t81WjFhQWaXFJCyC8sPbHdVGaLX7SmU0+Otck6QzaL+nWL8U7qHdGml+OhQkyoGgLojNAMA0IwYhqEPluzWE99sVLnLq+hQux4/r7/Gp3Qyu7QmY8mOPE2avkSS9O5Vx2tsr3iTK2o6yl0erc8s8I9Er9jt0L7iimrnJbQK8wfowZ1bqXf7KNlZiw8gQBGaAQBohrbnFuvumalanVEgSRo3sIP+77z+zbaRVX0pqXDrzy/+rLT9pZp0fKKevnCg2SU1aYZhKH1/mVak7feH6M1ZhfrDblcKD7Yp2bfdVZdWGtQ5lt9VAAGD0AwAQDPl8nj1yo/b9NIP2+TxGmoXHaJ/TEjWqB5tzS4tYD3833V6b/FudYypnJYdFcq07PpWVO7S6vQDo9Fp+VqVlq+icne187rHR/qndA/u0krd4iJYow/AFIRmAACaudXpDt01M1U79pVIkqaMSNL9Z/ZWWDDNmQ7267Z9unTGb5KkD64ZppE94kyuqGXweg1tyy32T+leuTvf/7t6sNjwIH+DscGdWyk5MUbhwWx3BaDhEZoBAGgBypwePT13o/69eLckqVvbCP1zYooGJsSaW1iAKCp36cx//qw9jjJNPrGz/u+8AWaX1KLlFVdoVZpDKw40GFud7lCFu2qDMZvVoj4dojSkc+VI9JAurdQplu2uANQ/QjMAAC3IT1tyde+nq5VTVCG71aLbTumhW04+rsU3YZo6e60+XpqmhFZhmn/naEWEMIIZSJxurzbuLfRP6V65O197C8qrndcuOkSDElsFTLfzqFC7TuoRp+Hd2rDtFtCEEZoBAGhh8kuc+tt/1unrtXslSSmJsXr+4mR1axtpcmXmWLglV1e8vVSS9PF1J2r4cW1Mrgi1keko8291tXJ3vtZnFsr9xw5jASLEbtWI49ro5N7xOrlXvBJbh5tdEoA6IDQDANACGYah/6Zm6qH/rlNRuVthQTb99ew+mjysc4ua3lpY7tKfXliovQXlmjIiSY+e28/sknCUypwerclwaO2egmpTuc2SkV+mBZtzqo2KH9c2Qif3itfJveN1fFJrBdtb9kwPINARmgEAaMEyHWW659PV+nV7niRpbK+2evbCgYqPDjW5ssZx32erNWt5hrq0CdfcO0bRWAr1zjAMbcku1o+bc/Tjphwt350vz0Ej4hHBNp3UPU4n947X2F5t1SEmzMRqARwKoRkAgBbO6zX07q+79PS8TXK6vYoND9KT5w/QWQM6mF1ag/pxU46ueneZLBZp5vXDdULX1maXhBagoMylRdv26cdNOfpxc672FVdUeb93+yj/NO7BnWNbfL8BIBAQmgEAgCRpa3aR7pyZqvWZhZKkCwZ10qPj+ym6Ge5VXFDq0hn//EnZhRW6ZmRXPTSur9kloQXyeg1t2Ft4IEDnaFW6Qwf/jTs61K5RPdvq5F6Vo9BxkSHmFQu0YIRmAADg53R79a/vt+rVBdvkNaSOMaH6x8XJGnFc89qz+O6ZqZq9ao+6xUXomztG0dkYAWF/iVM/b83Vj5ty9NOWXOWXuqq8n5wQozG94nVyr7YamBArm7Xl9B8AzERoBgAA1azYvV93z1qt3XmlkqRrRnbVvX/q1SzC5bfrs3T9+ytktUif3TRCgzu3MrskoBqP19DqDIcWHJjGvXZPQZX3W0cEa0zPtjq5d7xG94hTbHiwSZUCzR+hGQAAHFJJhVv/9/VGfbw0TZLUs12knr84Rf07xZhc2dHLL3Hq9BcWal9xhW4Y001T/9zH7JKAWskpKtdPm3O1YHOuFm7JVVGF2/+e1SIN7tzK30ysb4foFtUFH2hohGYAAHBY32/M1v2fr9W+4goF2Sy687SeunHMcU1yaujtH6/SF6sz1T0+Ul/dNrJZjJyj5XF5vFqxO18LNudqweYcbcoqqvJ+fFTIgS2t2uqk7nGKaoZ9CYDGRGgGAABHlFdcoamz1+rbDdmSpKFdWun5i1PUuU24yZXV3ty1e3XThytls1o0+6YRSk6MNbskoF5kOsoObGmVq0Xb9qnM5fG/Z7dadHxSa53cu7KhWPf4SEahgToiNAMAgFoxDEOfrcjQ37/coOIKt8KDbbr91B5qb+KezjarRaN7tlVM2OFH0vKKK3TGCwuVV+LULScfp3v/1LuRKgQaV4Xbo6U79+vHTZWj0Dv2lVR5v1NsmD9ADz+uDXuTA7VAaAYAAHWSvr9Uf5m1Wkt37Te7FEnSuIEd9PKlg2t83zAM3fLRSn2zNku920fpv7eepBA707LRMuzaV6IFmyubiS3ekSen2+t/L9hu1Ynd2ujkXpUhOikuwsRKgcBFaAYAAHXm8Rp6b/Eu/bApx7QaKtxeLd25XxHBNq18+PQag/CXqzN128erZLda9J9bTmrSjcyAY1Hm9Gjxjn36cVOuftyco4z8sirvd42L0NgDAfqErq1Z8w8cQGgGAABNktdr6IQnv9e+4gp9eO0wndS9+l7SOUXlOuOFhXKUunTHqT101+k9TagUCDyGYWh7brE/QC/btV8uz+9/3Q8Lsumk7m00tldlR+6EVk2nfwFQ32qbQ1nsAAAAAorVatHYXm312YoM/bgpp1poNgxDD85ZJ0epS307ROuWk7ubVCkQeCwWi7rHR6l7fJSuG91NReUuLdqWd2Aqd46yCyv0v405+t/GytkkPdtF6uRe8RrbK15Dk1opyGY1+TsAAg+hGQAABJyTe8XrsxUZWrAlV3/7w3v/Tc3UdxuyFWSz6B8TkhVs5y/5QE2iQoN0Zv/2OrN/exmGoY17i/Tj5hwt2JyjFbvztSW7WFuyi/XGwh2KCrFrZI+4AyG6reJNbAYIBBJCMwAACDgje8TJZrVoW06x0veXKrF15RTS7MJyPfLFeknS7af0UN+OLOsCastisahvx2j17Vg5Q6Og1KWFWyuncf+0OVd5JU7NXZelueuyJEn9Okb794VOSWzVJPdwB+oDoRkAAAScmLAg/X979x0fVZX3D/wz6b1OAkkISSAJIUhvIoQiNlCKFBuirOX3rLiCfW2I+rC6yqqLoruuBfSRBxX1sYEgKNJ7CAgkkEASEiCk90wymTm/P85M7gxkQoBJ5s7web9e8+KWkzvnzpfkzveec88ZHBeK3bnl+P1oMWaPiIcQAs99+weqGvToGxOMP4/t6ehqEjm1YD9PTOofjUn9o2E0CvxxqkrOC320BAcLK3H4dDUOn67G0o05CPHzxOikCIxLicDopAiEB3g7uvpEnYZJMxEREanS2F4Rcl7aoyWYPSIeX+8rxK9ZxfByd8Obt/Xns5dEduTmpkH/2BD0jw3Bo9clo7S2EZuPlWDj0RJsPlaCyno9fjhwGj8cOA2NBujfLaSlFfqq6GC4sRWaXBhHzyYiIiJVyjxTjQlLtsDH0w1r54/GpHe3oqaxGX+9KQUPsZX5ylFfDmStBnI2AFH9gbTH5fbSbGDdc23/7JT3gIBIubx+IVB8xHbZpBuAYQ/K5cJ9wO+v2S7r6Qvc/KZybCEAjesmjc0GIzIKKmUrdFYJjpypttqvDfDCmGSZQKclRSDY19NBNSW6OBw9uyPUlQEbF7VdZtRjQEh3ubx3GVB00HbZqAHA4HvlctUpYMd7gJef/EPs6W9aNr98gdjhchsANFQAGnfAyx9w41x7RETkelK6BqJrkA+KqnWY9dEu1DQ2Y0BsCB5MS3B01aij1ZcDmT8CR74DcjcDxubzy+iqgexf2j6O3mK+4sK9QP5W22XN398AoL4UyFlvu6zGDZj2H2X9w2vle0WmAJGpQGRvIKI3EJbgEt/TPNzdMCQ+DEPiw/DUjSkoqtJh0zGZQG/NKUVpbRO+SS/EN+mFcHfTYHD3UIxNkfNCp3QNhMaFbyjQlYEtzRejIg9Y0r/tMg9uBGIGyeUvZwOZP9gu2+dWYOZyuVywB/j4uraPPf8gEBonl5fdrPzhd/dSkmtzot13BjByvtxfdAjY/R+ZYJsTcC9/JTmPGQSE8449ERGpz7PfHsTK3QUAAC8PN6yZl4bEyAAH14o6zPGNwLYlMlEWBmV7l75A70lA3AggYbTcVlcKHFvb9vFSpwDegXI5ez1QW2y7rDYZiB0ql6sKgRObbJcVRmDQbLlsaAZejQYMjeeX8/CRxx37LJAyUW7TNwDu3oCbazxe0NRsxN78cvx+tAQbs4qRXVxrtb9rkA/GpURgbK9IjEzUIsCbbXakHmxp7gg+wfKPXlsCo5TlPrcCXfrYLhuRoiwHRMgkV98ANNUDetOrqU5u09crf/QBoNnizqmhSb50lco28wUFAMqPA+mftlFpDfCXPYA2qe1zIyIi6mRjkiNbkuanbujFhNnV1JUCuirl5n19GXBio1zu2hdInSpf2lbm4vbXAgPvbv97JV3f/rLB3YCBs9pX1s0dmJcOFGfK7t/FWfLfkqPy+9q5vQ43vQ7s/hCI6CVbpC1bpgO7Ol03by8PN1zTU4tremrx3MTeKCivx+/HSvB7VjG2HS9FUbUOK3cXYOXuAni6azCoeyhGJ0cgLUnLZ6HJabCl2VkJATQ3WiTX9YC+Tkm6g2PkH2BA/vHO/MEiAa8zlW+QFyc3d+C+tcpx87YC8aOc7o82ERG5noYmA+78cCe6BvngvVmDOOWNK6grld9LDn8nv3Mk3QDc9YXc11gje8elTnX+XnBGA1CZL7+HxQ4H/MPl9pV3AUdXt/4zPiFAv9uAiYvlenMj0Fir/KyT0ekN2JVbjo1Zxdh4tBj5ZfVW+0P9PDEyUduSREcF+zqopnSlam8eyqSZAL0O8DRNXn9iE/DZZHnX85p5wFXTAQ8vx9aPiIiInFttiUyUj3wnE2VhVPZ1Gwbct85luitfkEEPlJ84p1U6Cyg7LrukD7kfuOUtWTZvK7D8ZsA/4vxW6cgU2QvSieSX1WFLdik2HyvBjuNlqGm0flY9KTIAaUkRSEvWYnhCGPy82CmWOhaTZro06f8DrH0WaKqR60ExwNVz5YBllt3DiYiIiNrjyPfAqjnWiXLUAKDPVPnMcVgPB1VMZfQ6oCwb8PBVuqNn/C/w3UO2fyY4FnhkH+BhmjO5OAsIiZVj16ic3mDEgYJKbM4uxZbsEhwoqITRIivxcnfDkPhQmUQnaZEaFcSu3GR3TJrp0jVUAvuWATv/BdSeldt8goGhDwDD/6xMr0BERERkqeasbFHWNwAj58lt1WeAt3oD0QNMzyhPkaNKU/s01gKlR03PTJteJVlA9SkgJA541PTMtNEIvBYjP/vQuHNapXvLsWvMybUKVdXrsf14KTabWqJPVTZY7dcGeGFUorYliY4M8nFQTcmVMGmmy9fcCBz8Etj2jrzzCcjByq5/xbH1IiIiIvWoKZLTQx3+DsjfBkDIm+1P5iiPeNUUyUGuyH4aKmXjRkQvuV5zFvj3SKCupPXyGnfgrq+AJNNsLcVZcuqssB6Au7q6QQshkFsqu3JvyZZdueuaDFZlUroGIi1JJtHDEsLg4+n8U3tR52PSTPZjNAJH1wA73wemfwwEmUYIP/K97L7dbYhj60dERESdq74c+ONr+Yxy/nYAFl8nYwbLFuWh9ztFN2GXU1sClGRaPy9dfESOUv6XvcpsKV/MArJ+klOXapNNz0xbtEyHxKnmOfOmZiP2n6xoSaIPnqqCZQbj7eGGYQlhGG16HrpXF84NfUkMenlzxRz3ygKgodw0+HAD0Kwz/dsoR4YPTQB6jJFly47LQfzM5a5+CIge6LhzaScmzdSx9A3A21cB9aVA3EjZAp10A0fcJiIiclX6BsDTNLrx2SPAv0Yo+7oNNXW9ngyEdHdI9agNQsjW/oBIOWsKIJ8zP/aLnFWlNYP/BEz6p1yuOiW7hUemyAYTB3/fK69rwrYcmUBvyS7FmSqd1f6IQG+kJWkxOikCo5K00Aaot1t6q4SQ08k26+Sz7s0Nyr/NjbJ3gW+oLJu/Q94k0etk+ZbE1rQcnqQ8KlGRD3x9n0U5y2Pr5EB0c3cqM/CsuA3IXme7nv1uB6b9x1SP7cCyCcq+mZ/KcQtUjvM0U8dqqgOSbwQOfiW7YuVv44jbRERErqb6NHDENOp19Wlg/gGZMEX2BvrOlC1JvSfLwadIvTQapaeg2czlsjdh1cnzW6VLjsnWZ7Oc9cCP8+Wyd5CpRTpFeW46MhUIiOi00wnz98Kk/tGY1D8aQggcL6nF5mMyid55ohwlNY34Nv0Uvk0/BQDoEx2EtKQIjE7SYnB8KLw9LqIrtxAyoTQ0WY9Wfnq/aSpXi5ZXy8S257VK8pm1Gshao+yzarXVAaHxwJ0rZdmGSuD1eFj13jjX3d8CiePl8oGVQPqntsvGpylJszAAp/a2fb56i2fJ/bVAQFc5y46Hr+lf08vTF4jqr5QNjgVGPS63e/gAXfq0/T5Ohi3NdHmqTgG7/gXsXX7+iNvD/h+TZyIiImdTfVo+gnX4O6Bgp/W+ubtkayO5NkMzYNQrPQv2fw5sfxcozZaJ17mCYoDHj8hlIYB9y01JdYrSImoPRmPrraktyaoOjfHjsC+vApuzS+F56As0VBbDB03w0TTBG3r4u+kRG6hBTIAGPgNvQ9Tw6bIr96FvgE2LrVtezS8A8NMCTx9X6rKoqyxry5T3gIF3y+WNrwGb/m67bHgS8IgpmdXrgL91sdipMSWi3kriOmkJkDBa7t7zMZDzq43E1kd2oe47Q5ZtqgdObFSSXsty5p/1DlJ6I1wB2D2bOte5I26HJwEP71bNszBERER0ATVFwFf3AAW7rLfHXi27WfaeDATHOKRqpBLNTUBZjmmO6UylZTo8EZi1SpapKgTetmhlDIxSnpUO7CKTwhFzlalMf39dHuPc52XNifCAWcDYZ2TZIz8AX81uu44LSgF3T7m8ZABQkWuz6D/0M/G1/51IS9Libs+N6J+x0PZxvQKB5wqV9fevkXU2J58tSai3XB50j5LY5m8HTu6wbqW1TFh9guVYAIC86VBbrBzH3cvh3eFdGbtnU+fyDQFGPSZbmA9+Ke8qmhPms4eBXR/IrtvmeQeJiIjIsaoKgbytQP875Lp/BFBuSjCYKFNrPLyALqnyZcloMQe3XifHuSnOBKoKgJoz8nX8N6VM/zuUpDl3k2nUdRtqiy3e32KaKTcPi5ZVU0usp48czMqcNPeaKMffMbXSCg8flDW64URFM46WN2NnaTcUVeuwal8hNiMcPd2eR7eIEPSJ64L+CVFIjY2El4+/ksBamru9/Z9b3DXy1R4ajby5QKrClmbqeN/+F3DwCwAaoPctwMhHOeI2EZEtdWVAxgpl2pjuVwMpN8vl4kwg43/b/vnxC5XpY7YtAepKbZdNHA/0GCuXC/fJ51Zt8fAGrn1BWd/4qvWzb+fqPRmIHSqXT2wCcjbYLusXJm+8AoDRAGx4SXlPT1/A0w+IHaa0xNClqyyQXa+PfAcU7pHb5mUo8ybnbpathkHRjqohuRJdNVByVGmZbqiQie245+WgZABw+P/kiN/nPi9rXg7sqjwzb9DLlmgPH7tMk6XTG7AnrxxbTHNDZxXVWO3383LHiB7hclCx5AgkaP05KreLYUszqceQP8lpDo79LOdxzPxRGXE78Xp24SYiAuSXxh3vArs/sh7NtrlRSZrLc4Ht77R9nGtfQMvlPf0z2ZXSFu8gJWk+e6jtY3sFWifNuz4AdJW2y4clKEnzqb1tHzs0QUmahbBdtu9M4PpXmNBdrMqTyjPKVoMAaYDuI6zjaO5OSmQPPkHy74D5b0Fr+tza/uO5eyqtyHbg4+mOtKQIpCVF4LmJvVFcrcPWHJlAb80pRWltE37NKsavWbK1OybEF6OT5dzQI3tqEexnv7qQurGlmTpPcZYcROLgl3JwCUA+33LL20DciLZ/lojIVdUUyb+Nez5WBpXp2k9JXrqPkL10ANlSs//zto933ctKC8zWty/Q0nwd0HOcXC7cK1t8bPHwBsa/qKz/tqjtlubUKbJ1GABO/A5kr7dd1i8MSHtCLhsNwHrT+5ifbawrBY6tAyAAT3/g/22UU67QhTU3Aq8nWNyI0chuoqlTgd6Tzh9RmYgAAEajQGZRdcvc0HtyK9BkULqhu2mAft1CMDpJi7TkCAyIDYGnOxuCnA0HAiP1qj4tBwzbu0yOuG05H5wQHOyAiK4su/4D/PyUXI4ZDIz5K+e9b83p/cCap+Worn/6mZ9PayryZIty5k/AXV/KmxEA8PX98uZMn6kyUQ7s6shaEjmlhiYDduWWtXTlzi6utdof6O2BET3DkZYsp7aKC/d3UE3pYjBpJvXTVckh8q+aJteNBuDj64GEMcDwP3MQBCJyTZUFcnRi8xQgeh3wzf3yUZae45kMtkUI+UykORks3Af8/hpw02uANsmxdXOUijzZ7frId/LGgtnkpcAg0yjDRsMVNYUMUWc4U9VgaoUuxdbsElTU6632dw/zQ1qS7Mp9TWI4gnzYlVuNmDST8zm6Flh5u1x29wL638kRt4nIdVTkAVveUgbymp8BBHdzZI2c3ycTgJPb5Si6Vz8EjH5aPkN5Jdj+LvDH18CZDGWbxk2OGdJnKtB7ChAQ4ajaEV1RjEaBw6ersTm7BFuyS7AvvwJ6g5JiubtpMDA2RD4/naxFv5hgeLArtyowaSbnYzTKwcK2/hMo3G3aqJED4Ix6jCNuE5FzKjsuk+UDKwFhkNsSxgAT/wFEJDu2bs6u7Diw7jng2Fq57h8JXP8y0O8O1xtksuy4vMni4S3XP50sp+rRuAHxo0zPKE9mokykArWNzdh1wtSVO7sEJ0rqrPYH+XhgZKLWNAiZFrFhfg6qKTFpJueWv0NOlXLsZ2Vb6lTgtk8dViUiootScgzY8g/gj1WAMA0e03M8MOZpOY0U2c+xX4C1zwDlx+V6zBBg4hvOP0VV2XE5ONuR74CiP4A7VgIpE+W+Y78A1YVAyiQmykQqV1hRj63mrtw5pahqsO7KnaD1lwOKJUXg6p7hCPDmBEedhUkzuQbLEbfHPauMrqqrNs3f5+XY+hER2fI/twLHf5PLSTfKZJk9ZjpOc6McZHLzYqCpVl4jHjsC+Ic7umYXpzQHOPJ/wOHvgbN/KNs17sD4BcrUXETklAxGgYOFlS2jcqefrITBqKRjHm4aDIoLbUmir4oJhrsbx7roKEyaybVUnwa8/AGfYLm+7nng0LfAiLnA4DmAd6BDq0dEhKI/AGMzED1QrudvB7YvBcY8pWyjjld9BtjwkpzL+bqFcpuhGYCw6/yuHeLr+4BD3yjrGnegxxjZ0yrlFue7AUBEF1Sj02PH8bKWJDqvrN5qf4ifJ0YmajEmKQKjkrSIDvF1UE1dE5Nmcl1GA/DeMKAsR657BwND7+eI20TkGKczZOtm1k9At2HA/b9wBGw1sJzCcMd7wL5PgQl/B3pe69h6mZUck92uk28EovrLbZsXAxtfY6JMdAU7WVbfMqDY9pwy1DQ2W+1PjAxAWpIWo5MiMLxHGPy82JX7cjBpJtem18ku29vfUZLnlhG3H7lypx4hos5TuA/Y/IYyCBU0QJ9bgSlLZc8YUgejAVg6BCg/IddTbgFuWASEJXR+XUqOKtNDFR+R266eK6fMAoD6cvmveUotIrqiNRuMOFBYic3HZCt0RkElLHpyw8vdDYPjQpGWLJPo1KgguLEr90Vh0kxXBqMROLoG2PZPoHCPaaMGeGg70CXVkTUjIldVsBvY9DqQs0Gua9yAvjPlmAsRvRxbN2pdQ6WM2a4P5Ajm7t7AyHny+eCOvsFRmiO7XFsmyoCcJqvHWGDQPUDqlI6tAxG5hKp6PbYfL8Xm7FJsPlaCU5UNVvvD/b0wKkkZlbtLkI+Dauo8mDTTlUUI4OROmTzXlQIPbJDd8oSQzxXGXcPukkR0+Roqgbd6A/p6+bxp/ztkshze09E1o/YozgJ+flpO1QQAQTHADf8N9Jlm32uEoRlwN3WZXPsssPN9uezmKRPlPlOBXhPZokxEl0wIgbyyemzJLsHmY6XYcbwUdU0GqzK9ugQiLUmLtOQIDE8Ig4+nu4Nqq15MmunKpdcBnqY7a/k7gGU3AZGpwDXzgKumc8RtImo/IYDczUDMIGXAwQ0vAfVlwKjHHdPFly6PEPL583XPAZUngbCewNydl39tKM5Uul5fNUMOAAcABXtkN/7UqXK6KN/QyzwBIqLz6Q1G7D9Zic3H5PPQB09VwTLL8/Jww/CEMJlEJ0UgpWsgNGxQYtJMBADIWAmseQpoqpHrQTHy+bHB93LEbSKyTQg5XdSmN4CCncB1LwOjHnV0rcie9A1ySsPoQUDSdXJbTZEcH6M9LcBCyET5yHcyWS49quyLGgD816YOqDQRUftU1DVh2/FSbDlWis3ZJThTpbPaHxHojbRELdKStRiVGIGIQG8H1dSxmDQTmTVUAvuWyfk7a8/KbRxxm4haIwSQvV4+/3pqr9zm7i2ffR33rGPrRh3vy7uBvK3AtS8Ag/8EuNnoynjkB+C3/wZKjynb3L3kyNypU4FeEwDfkM6oMRHRBQkhcLykztSVuwQ7T5SjQW/dlbt3VBBGmwYUGxwXesV05WbSTHSu5kY54va2d4CybLnt6oeBm151bL2IyPGEkIMKbnoDOJMht3n4AkPukwNGBXZ1aPWoE+iqgU9uAooPy/UufYEJr8sxMc4elteQboPlvqw1wBd3ykQ58TpTonwT4BPssOoTEbVXY7MB+/IrWuaGPnSq2mq/j6cbhieEy6mtkiOQFBngsl25mTQT2WI0Asd+BrYvBaZ9AIR0l9uzVgMBXYBuQxxbPyLqfOYkCAA8/YChD8jp6wIiHVsv6lyGZtkz6bdFgK5SbguKAapPAQmjgXt/lNv0OiDzByD5JsCH31uIyLmV1jZiW05pSxJ9trrRan/XIJ+WAcVGJWoR5u864wMxaSa6GM2NwD/7AbVFQNxIYOR8IPF6wM3N0TVzLPOfBxe9u0hXMKNBTlPX/Wpl/cNrZffaEQ8D/lrH1o8cq64M2LgI2LsMgJBd9JNvBGYut91lm4jIBQghcOxsrezKnV2KXSfK0NhsbNmv0QBXRQe3DCg2OC4UXh7O+32ZSTPRxagvB35ZILtvG/VyW0Rv2S3zqhmuNeK2EEBTLVBbLJ/xri2Wr2EPKsnx/94BFB2U20O6A7d+AMQOdWy9iezB0CznzN3yD6A0W46aHJki9xmNvFFG1kqOAuW5sos2W5SJ6Aqk0xuwN6+iJYnOPGPdldvPyx1X9wjHaFNLdA+tv1N15WbSTHQpqk/LAcP2Ljt/xO1hDwIeKh5ZUN8gk9y6EpkM+2mB7sPlvlPpwM9/ldvrSuQcs+d6OlcZMfY/44DT6co+N0/gxletE2siZ2LQAwe/ksly+Qm5zScYmPIe0HuSY+tGRETkJIqrddhq0ZW7tLbJan9MiG9LK/TIxHCE+Km74YlJM9HlOHfE7dB44JH0zu+WZ9ADdaVKi3DsMGVE1i1vATkblJbixirrn+0zDZi5TC6fSgc+HGe93ytAPq8Z0AXwjwAm/kMZSbxwH6AB4BMC/PoycOR7uf2qGcDkdwAv/w46YSI7a24CDn4BbHkTqMiT23zDgGv+Agx9kK2HREREl8hoFMgqqsGW7BJsyS7F7rxyNFl05X5mQgr+PKanA2t4YUyaiezBPOK2dyDQ51a5reQYsGMpcM08QJt48cc0GoGGcpkIG5qA6IFye0MFsOZpoK5Y6TpdX2b9s3PWAPEj5fJ3c4GMFdb73b1lEhwQAfQYC4x/UW7XVQMnfjfti5Sv9ia+QgA735fd14UBiE+Tg+GwxZmcwU+PA3s/lst+WvnIxZD7Ae8Ax9aLiIjIxTQ0GbArt6ylFfqftw9EarS6czsmzUQd5fu/APv/B4AGSLkZGPmoHHFbVyWTXb9wwD9cls1eDxz+ztRSfFbpPi1Mc+NF9AYe3imXm+qBV6POfz+Nu2wJDogEbvq7kjSf3ClHdA3oAvibEmGf4I5LZvO3A988ILuz9hx34fJEjqDXAVWFyg2ts4eBz6fLkbAH/wnw8nNs/YiIiEg1mDQTdZSTu4Ctb8tpq8zcvWSrMSC7OQ97UC5vfxf45YXWj+MXDmh7AfdZHGfH+3J7QISpVbiL7EqqlsGJ9DrA00dZP/QtoE0G3DzOL6vRABG9lPXSbDlCsS0Bkcoz1fXl8gaDLW4e1q38xVlt1zsoSpk/tbZYHr+9xybn0FQP7FsObFsiYz13p/J7Y9AD7p4OrR4RERGpT3vz0Fa+6RJRm7oPB+76QiZq29+V3bfNCbN3sPyCbhY3Erh2gZIAm7tG+0e0/iV+xNzOOYdLZZkw//E18M39tsu6ewMLLBLfZRNl13NbJrwBDP8vuZyxwvbNBgAI6gY8flhZf/9qAG3c/5v+MdB3hlze8R6w7Z+2y4YnAY/slcvNjcBnU4DArkBgtEy+A6OAoGj5b2CU9WdCna+xVna/3v6u7MUByN+tynwgLEFZJyIiIrpETJqJLlVkCjD1PeCG/wYaa2Qy7OlrXSZmkHy5Ig8fIKwnoKtsfb/7OSON+4Up3dJbPZ5FeQ8f2eJui2/oOccOR5tJs+WxvfzbPrZl63hNEXByh+2yADBnNRA/Si5nrAQqck1JtTnJjpbnzmfA7UtXDez5ENi+VI4RAAAhcUDaE0D/O11rmjgiIiJyKHbPJiKyRVcNHP8VqD4D1Jw2/XtGTk1WcwZo1gF/2Qtok2T5FTOB7F/OP467t2yt7jsTGL9AbqstBnI3ywTbO0jecPH0lTcMPP1kos9Eu3VGI7B0CFB+XK6H9QDSngT63cZWZSIiImo3ds8mIrpcPkHKqOnnEkKOeG5+VhqQA8MFRVsn2fWlgKFRdhduqlXKnt7fdvd2aIDnzyi9Fz6fAdQWAR6+SoLt6ausp0wEEq+TZYuzZAu5ZRLuaU7GfeRgWGE9lLdqqmv7c3D3UpLR5ibAqG+jsEYZbEuI1ucEtzq2N+DuoZS3daOgvhzQuMkp19zcgAF3Age+BEY/BVw1XTkGERERkZ3xWwYR0aXQaJSBy8wGz5EvS82Nspt3zRk5qJuZh4985r3mjHwut1knE0xjs6mAkGXMSo4CVSdt1yckVkma87cCq5+wXdYnGHjG4lhv9ASaG2yXn/I+MHCWXN7yJrDp77bLRqQAD++Sy/p64NVo22UB4K5VQPINcvnnv8rnk83JvWWiX3YcGHo/cP3LsuyIR4BRj3f+3OlERER0xWHSTETUkTy8gdA4+bLUY4x8ncugB/QNMom2bHWd8QnQWCX36XUyydVbvLqPUMoGdwd63Xx+GfO6Zeu4mjQ3yJsGjdXyda6TO5TWaA7ARkRERJ2EzzQTEV3pmi7UhdpL6f5s0FuPEH8ujUbpUi6ETNLb4uGttBY31siXZaKvr5c3ELwDgdir1TP9GhERETk9PtNMRETtY34GuT3cPds/2JZGc3HH9g6ULyIiIiIV4S17IiIiIiIiIhuYNBMRERERERHZwKSZiIiIiIiIyAYmzUREREREREQ2MGkmIiIiIiIisoFJMxEREREREZENTJqJiIiIiIiIbLBb0pyeno4BAwbA19cXN9xwA4qLi+11aCIiIiIiIiKHsEvSbDQaMX36dNxyyy3Izs6Gr68vHnvsMXscmoiIiIiIiMhhPOxxkE2bNqG8vBwvvfQSPDw8sHDhQowaNQp1dXXw9/e3x1sQERERERERdTq7tDRv27YNw4YNg4eHzMEHDBgAg8GA9PT0Vss3Njaiurra6kVERERERESkNnZJmouKiqDVapWDurkhNDQUZ8+ebbX8a6+9huDg4JZXbGysPapBREREREREZFd2GwhMCHHeukajabXss88+i6qqqpZXQUGBvapBREREREREZDd2eaY5KioKmZmZLesGgwGVlZXo2rVrq+W9vb3h7e1tj7cmIiIiIiIi6jB2aWlOS0vDnj170NzcDADYv38/PDw8MHDgQHscnoiIiIiIiMgh7JI0jxo1ChEREVi4cCEKCwvxyiuvYNq0afDz87PH4YmIiIiIiIgcwi5Js5ubG1atWoWffvoJiYmJ0Ol0eOutt+xxaCIiIiIiIiKHscszzQAwaNAgHDhwwF6HIyIiIiIiInI4u42eTURERERERORqmDQTERERERER2cCkmYiIiIiIiMgGJs1ERERERERENjBpJiIiIiIiIrKBSTMRERERERGRDXabcupyCCEAANXV1Q6uCREREREREV0JzPmnOR+1RRVJc01NDQAgNjbWwTUhIiIiIiKiK0lNTQ2Cg4Nt7teIC6XVncBoNOL06dMIDAyERqNps2x1dTViY2NRUFCAoKCgTqohtYaxUA/GQh0YB3VgHNSF8VAPxsLxGAP1YCzUw5GxEEKgpqYG0dHRcHOz/eSyKlqa3dzc0K1bt4v6maCgIP4HVwnGQj0YC3VgHNSBcVAXxkM9GAvHYwzUg7FQD0fFoq0WZjMOBEZERERERERkA5NmIiIiIiIiIhucLmn29vbGwoUL4e3t7eiqXPEYC/VgLNSBcVAHxkFdGA/1YCwcjzFQD8ZCPZwhFqoYCIyIiIiIiIhIjZyupZmIiIiIiIioszBpJiIiIiIiIrKBSTMRERERERGRDUyaiYiIiIiIiGzosKT5xIkTGDNmDAIDAzF27Fjk5+cDANatW4fk5GT4+/vjjjvuQH19fcvPrFu3DikpKQgJCcGcOXOg0+msjvnbb7/hmmuuaXcdhBB44oknEBwcjOjoaHz88cct+8aOHQuNRmP1Wr58+eWdtEqpIRYAYDAY8MUXX2DatGlW23U6He699174+/ujR48e+Omnny7xTJ2DvePx2WefISEhAVqtFk8++STaM7ZfW78bANDU1IQ333wTjz76qH1OWmWcIQaAjEPv3r0xZ86cyz9plVJ7LHit6NxYALxWmNk7Hh988AFiYmIQHh6OefPmwWg0tqseixcvRmRkJMLCwrBo0SKrfbZi5SqcIQZm48ePx9ixYy/9ZFVM7XGYM2fOedeJl156yT4nr0JqiQfQej7Snu9Xl0R0kPHjx4u7775b5OXliWnTpombb75ZVFRUiKCgIPGvf/1L5ObmiuHDh4vnnntOCCFEdXW1CAkJEe+88444evSo6Nmzp1i8eHHL8by8vAQA0b9//3bX4ZNPPhGxsbHi4MGDYu3atcLHx0dkZmYKIYSoqakRFRUVoqKiQpSWlorg4GCxdu1au34GaqGGWOTn5wsPDw8BQEyZMsVq34svvigGDhwocnJyxPLly0VgYKAoKyuzx6mrkj3jkZubKzw9PcU333wj0tPTRWhoqFi1atUF69DW78aWLVuEu7u7ACDmz5/fYZ+DI6k9BmZ/+9vfBABx77332v0zUAu1x4LXis6NBa8VCnvGIz09XWi1WrFr1y5x+PBh0b17d/HZZ59dsA6//fabCAoKElu2bBG7d+8WoaGh4pdffhFCtB0rV6H2GJitWLFCABBjxoyx+2egBmqPQ11dXct1oqKiQqSmpop///vfHfeBOJga4iGE7XykPd+vLkWHJM2NjY1Co9GIw4cPCyGEWL16tQgKChKffPKJSE1NbSn3zTffiO7duwshhFi/fr2IjIxs2ffUU0+JyZMnt6zn5uaKxYsXX1SiNnr0aPHGG2+0rE+aNEksWLDgvHJbt24Vvr6+oqGhod3HdhZqiYVerxe5ubli/vz5511c4+LixFdffdWy3rdvX/Hxxx9fzGk6DXvH48MPPxRDhw5t2Tdz5kwxb968C9ajrd+NhoYGkZubK6ZPn+6SSbMzxEAI+XsWGhoqJkyY4LJJs7PEwozXio6PBa8Vkr3jsWLFCvHiiy+27Js5c6Z45plnLliPe+65R8ydO7dl/ZFHHhGzZ88WQrQdK1fgDDEQQoiqqioRFRUlpk6d6pJJs7PEwaywsFAAEHl5eRd5ps5BLfEQwnY+0t5r+sXqkO7Zer0eb7zxBhISEgAAZWVl8PX1xbZt26ya0IcPH46TJ0+ioKAA3bp1w+uvv96yz/wzZvHx8dBqte2ugxACO3bsOO/9tm3bdl7ZNWvWYNy4cfDx8bmo83QGaogFAHh4eCA+Ph4hISFW2wsLC5Gfn9+uOLkCe8ejb9++eOaZZ1rdZ8uFfjd8fHwQHx+PgICAyz9hFXKGGADA/Pnz8fDDDyM5OfnyTljFnCUWZrxWdGwsAF4rzOwdj7vuugsvv/wyACAvLw9btmzBwIEDL1iP1t7P/JnbipWrcIYYAMCCBQswfvx4jBkz5vJOWKWcJQ5ma9asQWpqKuLi4i7thFVOLfEAWs9HLuaafrE8LvsIrfD398eTTz4JQH64S5YswezZs5GZmYm+ffu2lAsPDwcAnD17FkOGDEFKSgoAID8/H6tWrcLKlSvbfJ/MzEyMGDGi1X05OTnQ6/VWH2Z4eDjOnj17XtnVq1fjgQceuLiTdBJqiEVlZaXNnysqKgKA8+J06NChC5+cE7J3PIYPH97yM3v27MHWrVvx9ttv2+13wxU5Qwx++uknHDp0CF988QWeffZZO569ujhDLCzxWtGxseC1QtFR1+7PP/8cs2fPxowZM3Dbbbehrq4OMTExrdbh4MGDKCoq4rUC6o1BRkYGVqxYgcOHD1/we5qzcoY4WFq9ejUmTJhweSetYmqJR/fu3VvdV1ZW1mHfcTskaTZrbm7GnXfeCXd3d7zyyiuYOXOm1UAg5mWNRtOy7cyZM7jxxhsxZ84c3HzzzW0ePzExERkZGW2WOff9LN8LAE6fPo0DBw5g4sSJ7T0tp6SGWLTlQnFyNfaOR2ZmJiZNmoTXXnsN/fr1g16vv+zfDVen1hg0NDTgkUcewdKlS9vVMucK1BoLS7xWSJ0Ri7ZcaX+37B2PyZMn4/vvv8d9992Hr7/+GtOnT7cZj+joaKv3MC+7+md+LrXGQAiBhx56CC+//DK6dOlir9NVLbXGwVJTUxN+/fVXzJs377LO1RmoIR5t6Yi/Wx2WNBuNRtx+++3Iz8/H+vXr4evri6ioKJSUlLSUKSsrAwB07doVAFBcXIyxY8ciLS0NS5YsueB7eHp6Ij4+vtV9Qgh4eXmhpKSk5e5GWVlZy3uZrVmzBsnJyejRo8elnKZTcHQs2hIVFQUAKCkpQWxsbEtdzo2TK7F3PI4ePYpx48Zh7ty5ePzxxwHY53fDlak5Brt370ZeXh5mzZoFAGhoaIAQAqWlpS45WrCaY2GJ1wqpI2PRFl4rLi8ehw4dQlhYGKKjozF58mTMmjULK1aswIwZM9qMR2vv58qf+bnUHIOTJ09i586dOHLkCJ5//nk0NjZCr9ejX79+OHjwoJ0/CcdScxwsbd68GRqNBqNGjbLHaauWGuJhS3h4eId9x+2wKacWLFiA48eP49dff0VoaCgAIC0tDdu3b28ps3PnTsTHxyMmJgZGoxHTp0/HyJEj8eGHH172HQGNRoORI0ee937n/kdevXq1y7ccODoWbYmJiUFCQsIF4+RK7BmP+vp6TJo0CQ899BBefPHFdr1/e383XJmaYzB8+HDk5uYiIyMDGRkZmDVrFiZPnoyPPvrITmevLmqOhSVeK6SOjEVbeK24vHi8+uqrWLp0acu6RqOBu7v7BevQ2vu58md+LjXHICYmBrm5uThw4AAyMjLw1FNPYciQIVizZo09Tl1V1BwHS6tXr8b48ePh5eV1yefqDNQQD1s69DvuZQ8l1oq8vDzh4+Mjtm/fbjUEe2VlpQgODhbvv/++yM3NFcOGDRMvvPCCEEKIzz//XHTv3l2cOXOmpXxVVZXVcZctW3ZRIzYvW7ZMdOvWzWrI8aysrJb9jY2NIjAwUKxbt84u561GaomF2cKFC88bZXPhwoViwIABIicnRyxbtkwEBgaK8vLySz1lVbN3PBYtWiSGDh0qysvLW/bV1NRcsB4X+t0QQoh7773XJUfPdqYYCCHE/PnzXXb0bGeJBa8VnRcLM14r7BuPTz/9VMTGxor09HSxf/9+ERMT066Rxzdu3CgCAwNbptkJCQkRGzZssCrTWqxcgTPFQAgh3n77bZccPduZ4pCcnCw++OAD+38IKqKWeJi1lo+09/vVxeqQpHn58uUCwHmv3NxcsW7dOpGYmCh8fX3F7bffLurq6oQQQsyZM+e88nFxcVbHvdhEzWg0iieeeEIEBQWJrl27io8++shq/4YNG4Sfn5/Q6XSXe8qqpZZYmLV2cW1oaBD33HOP8PPzE/Hx8eLHH3+8xLNVP3vHY+zYsefta89F80K/G0K4btLsTDEQwrWTZmeJBa8VnRcLM14r7BsPo9Eonn/+eREZGSkiIyPF888/L4xGY7vqsnjxYhEeHi5CQ0PFokWLztvvqkmzM8VACNdNmp0lDjk5OQKAKCgosOv5q42a4iFE6/lIe79fXSyNEBZPShMRERERERFRiw57ppmIiIiIiIjI2TFpJiIiIiIiIrKBSTMRERERERGRDUyaiYiIiIiIiGxg0kxERERERERkA5NmIiIiIiIiIhuYNBMRERERERHZwKSZiIiIiIiIyAYmzUREREREREQ2MGkmIiIiIiIisuH/A7mhMKvzvvJvAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "from IPython.display import display\n",
    "from dataModel import JJs, Stocks, db\n",
    "\n",
    "\n",
    "# 忽略警告\n",
    "from warnings import simplefilter\n",
    "simplefilter(action='ignore', category=FutureWarning)\n",
    "\n",
    "matplotlib.use(\"TkAgg\")  # 大小写无所谓 tkaGg ,TkAgg 都行\n",
    "plt.rcParams[\"font.family\"] = [\"sans-serif\"]  # 用来正常显示中文标签\n",
    "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"]  # 用来正常显示中文标签\n",
    "plt.rcParams[\"axes.unicode_minus\"] = False  # 用来正常显示负号\n",
    "%matplotlib inline\n",
    "\n",
    "name=\"中远海控\"\n",
    "\n",
    "sSelect = Stocks.select()\n",
    "print(\"开始查找股票数据...\")\n",
    "dates=[]\n",
    "datas = sSelect.where((name == Stocks.name))\n",
    "datas_dict={\n",
    "    '持有基金个数':[],\n",
    "    '持有基金市值':[],\n",
    "}\n",
    "for stock in datas:\n",
    "    stock:Stocks\n",
    "    dates.append(pd.to_datetime(stock.date))\n",
    "    datas_dict['持有基金个数'].append(stock.n)\n",
    "    datas_dict['持有基金市值'].append(stock.money)\n",
    "\n",
    "df = pd.DataFrame(datas_dict)\n",
    "df.index=dates\n",
    "print(\"数据查找完毕，开始绘图...\")\n",
    "\n",
    "fig = sns.lineplot(data=df)\n",
    "fig.get_figure().set_figwidth(12)  # 设置宽度\n",
    "fig.get_figure().set_figheight(8)  # 设置高度\n",
    "plt.title(f\"{name}基金持仓变化\")\n",
    "plt.show()\n",
    "\n",
    "\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 三、总量统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m2023-09-20\u001b[39m股票型基金总数量为\u001b[34m2550\u001b[39m个，总规模为\u001b[31m14249.920\u001b[39m亿元。\n",
      "\u001b[32m2023-05-29\u001b[39m股票型基金总数量为\u001b[34m2472\u001b[39m个，总规模为\u001b[31m14634.300\u001b[39m亿元。\n",
      "\u001b[32m2023-03-18\u001b[39m股票型基金总数量为\u001b[34m2390\u001b[39m个，总规模为\u001b[31m14264.360\u001b[39m亿元。\n",
      "\u001b[32m2022-11-14\u001b[39m股票型基金总数量为\u001b[34m2333\u001b[39m个，总规模为\u001b[31m13881.490\u001b[39m亿元。\n",
      "\u001b[32m2022-10-14\u001b[39m股票型基金总数量为\u001b[34m2248\u001b[39m个，总规模为\u001b[31m15168.700\u001b[39m亿元。\n",
      "\u001b[32m2022-09-14\u001b[39m股票型基金总数量为\u001b[34m2200\u001b[39m个，总规模为\u001b[31m15138.830\u001b[39m亿元。\n",
      "\u001b[32m2022-08-15\u001b[39m股票型基金总数量为\u001b[34m2239\u001b[39m个，总规模为\u001b[31m15512.020\u001b[39m亿元。\n",
      "\u001b[32m2022-06-13\u001b[39m股票型基金总数量为\u001b[34m2153\u001b[39m个，总规模为\u001b[31m13931.540\u001b[39m亿元。\n",
      "\u001b[32m2022-05-12\u001b[39m股票型基金总数量为\u001b[34m2129\u001b[39m个，总规模为\u001b[31m13912.970\u001b[39m亿元。\n",
      "\u001b[32m2022-03-18\u001b[39m股票型基金总数量为\u001b[34m1819\u001b[39m个，总规模为\u001b[31m14395.910\u001b[39m亿元。\n",
      "\u001b[32m2022-01-21\u001b[39m股票型基金总数量为\u001b[34m1849\u001b[39m个，总规模为\u001b[31m15231.680\u001b[39m亿元。\n",
      "\u001b[32m2021-12-01\u001b[39m股票型基金总数量为\u001b[34m1877\u001b[39m个，总规模为\u001b[31m15259.510\u001b[39m亿元。\n",
      "\u001b[32m2021-09-17\u001b[39m股票型基金总数量为\u001b[34m1690\u001b[39m个，总规模为\u001b[31m14064.090\u001b[39m亿元。\n",
      "\u001b[32m2021-07-30\u001b[39m股票型基金总数量为\u001b[34m1638\u001b[39m个，总规模为\u001b[31m14310.640\u001b[39m亿元。\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "from IPython.display import display\n",
    "from dataModel import JJs, Stocks, db\n",
    "from colorama import Fore\n",
    "\n",
    "# 忽略警告\n",
    "from warnings import simplefilter\n",
    "simplefilter(action='ignore', category=FutureWarning)\n",
    "\n",
    "\n",
    "#import matplotlib    \n",
    "#print(matplotlib.matplotlib_fname())# 获取mpl目录\n",
    "\n",
    "\n",
    "matplotlib.use(\"TkAgg\")  # 大小写无所谓 tkaGg ,TkAgg 都行\n",
    "plt.rcParams[\"font.family\"] = [\"sans-serif\"]  # 用来正常显示中文标签\n",
    "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"]  # 用来正常显示中文标签\n",
    "plt.rcParams[\"axes.unicode_minus\"] = False  # 用来正常显示负号\n",
    "%matplotlib inline\n",
    "\n",
    "dates=[\n",
    "    \"2023-09-20\",\n",
    "    \"2023-05-29\",\n",
    "    \"2023-03-18\",\n",
    "    \"2022-11-14\",\n",
    "    \"2022-10-14\",\n",
    "    \"2022-09-14\",\n",
    "    \"2022-08-15\",\n",
    "    \"2022-06-13\",\n",
    "    \"2022-05-12\",\n",
    "    \"2022-03-18\",\n",
    "    \"2022-01-21\",\n",
    "    \"2021-12-01\",\n",
    "    \"2021-09-17\",\n",
    "    \"2021-07-30\",    \n",
    "]\n",
    "\n",
    "sSelect = Stocks.select()\n",
    "\n",
    "jSelect=JJs.select()\n",
    "datas={\n",
    "    \"股票型基金数量\":[],\n",
    "    \"股票型基金规模\":[],\n",
    "}\n",
    "for date in dates:\n",
    "    jjs=jSelect.where((date==JJs.date))\n",
    "    stocks = sSelect.where((date == Stocks.date))\n",
    "    规模=0\n",
    "    for jj in jjs:\n",
    "        规模+=jj.money\n",
    "    datas[\"股票型基金数量\"].append(len(jjs)*10)\n",
    "    datas[\"股票型基金规模\"].append(规模)\n",
    "    print(f\"{Fore.GREEN}{date}{Fore.RESET}股票型基金总数量为{Fore.BLUE}{len(jjs)}{Fore.RESET}个，总规模为{Fore.RED}{规模:.3f}{Fore.RESET}亿元。\")\n",
    "df=pd.DataFrame(datas)\n",
    "dates=[pd.to_datetime(d) for d in dates]\n",
    "df.index=dates\n",
    "fig = sns.lineplot(data=df)\n",
    "fig.get_figure().set_figwidth(12)  # 设置宽度\n",
    "fig.get_figure().set_figheight(8)  # 设置高度\n",
    "plt.title(\"股票型基金持仓总规模变化\\n数量扩大10倍(绘图方便)\",ha=\"center\")\n",
    "plt.show()"
   ]
  }
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